End of training
Browse files- .hydra/config.yaml +18 -0
- .hydra/hydra.yaml +166 -0
- .hydra/overrides.yaml +1 -0
- README.md +55 -180
- logs/events.out.tfevents.1716473018.rnn.ist.berkeley.edu.3033116.0 +3 -0
- model.safetensors +1 -1
- special_tokens_map.json +24 -0
- tokenizer.json +0 -0
- tokenizer_config.json +216 -0
- train.log +1 -0
- training_args.bin +3 -0
.hydra/config.yaml
ADDED
@@ -0,0 +1,18 @@
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model:
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dataset_name: redwoodresearch/diamonds-seed0
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model_type: gpt_neox
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pretrained_model_name: EleutherAI/pythia-14m
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max_length: 2048
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hparams:
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learning_rate: 2.0e-05
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weight_decay: 0.02
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lr_scheduler_type: cosine
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warmup_steps: 64
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effective_batch_size: 32
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num_train_epochs: 5
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per_device_train_batch_size: 1
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per_device_eval_batch_size: 1
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num_epochs: 1
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fp16: false
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dataset_len: 2
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push_to_hub: true
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.hydra/hydra.yaml
ADDED
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hydra:
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run:
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dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
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sweep:
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dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
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subdir: ${hydra.job.num}
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launcher:
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submitit_folder: ${hydra.sweep.dir}/.submitit/%j
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timeout_min: 60
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cpus_per_task: null
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gpus_per_node: null
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tasks_per_node: 1
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mem_gb: null
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nodes: 1
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name: ${hydra.job.name}
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stderr_to_stdout: false
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_target_: hydra_plugins.hydra_submitit_launcher.submitit_launcher.LocalLauncher
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sweeper:
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_target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
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max_batch_size: null
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params: null
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help:
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app_name: ${hydra.job.name}
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header: '${hydra.help.app_name} is powered by Hydra.
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'
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footer: 'Powered by Hydra (https://hydra.cc)
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Use --hydra-help to view Hydra specific help
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'
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template: '${hydra.help.header}
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+
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== Configuration groups ==
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Compose your configuration from those groups (group=option)
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$APP_CONFIG_GROUPS
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+
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== Config ==
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Override anything in the config (foo.bar=value)
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$CONFIG
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${hydra.help.footer}
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'
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hydra_help:
|
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template: 'Hydra (${hydra.runtime.version})
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See https://hydra.cc for more info.
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== Flags ==
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|
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$FLAGS_HELP
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+
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== Configuration groups ==
|
65 |
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|
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Compose your configuration from those groups (For example, append hydra/job_logging=disabled
|
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to command line)
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$HYDRA_CONFIG_GROUPS
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|
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Use ''--cfg hydra'' to Show the Hydra config.
|
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'
|
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hydra_help: ???
|
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hydra_logging:
|
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version: 1
|
79 |
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formatters:
|
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simple:
|
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format: '[%(asctime)s][HYDRA] %(message)s'
|
82 |
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handlers:
|
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console:
|
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class: logging.StreamHandler
|
85 |
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formatter: simple
|
86 |
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stream: ext://sys.stdout
|
87 |
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root:
|
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level: INFO
|
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handlers:
|
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- console
|
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loggers:
|
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logging_example:
|
93 |
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level: DEBUG
|
94 |
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disable_existing_loggers: false
|
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job_logging:
|
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version: 1
|
97 |
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formatters:
|
98 |
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simple:
|
99 |
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format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
|
100 |
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handlers:
|
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console:
|
102 |
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class: logging.StreamHandler
|
103 |
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formatter: simple
|
104 |
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stream: ext://sys.stdout
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file:
|
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class: logging.FileHandler
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formatter: simple
|
108 |
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filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
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109 |
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root:
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level: INFO
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handlers:
|
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- console
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- file
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disable_existing_loggers: false
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env: {}
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mode: RUN
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searchpath: []
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callbacks: {}
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output_subdir: .hydra
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overrides:
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hydra:
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- hydra.mode=RUN
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task:
|
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- push_to_hub=true
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job:
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name: train
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chdir: null
|
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override_dirname: push_to_hub=true
|
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id: ???
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num: ???
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config_name: pythia_diamonds_local_test
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env_set: {}
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133 |
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env_copy: []
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config:
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override_dirname:
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kv_sep: '='
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137 |
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item_sep: ','
|
138 |
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exclude_keys: []
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139 |
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runtime:
|
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version: 1.3.2
|
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version_base: '1.1'
|
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cwd: /nas/ucb/oliveradk/measurement-pred
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config_sources:
|
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- path: hydra.conf
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schema: pkg
|
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provider: hydra
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- path: /nas/ucb/oliveradk/measurement-pred/conf
|
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schema: file
|
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provider: main
|
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- path: ''
|
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schema: structured
|
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provider: schema
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output_dir: /nas/ucb/oliveradk/measurement-pred/outputs/2024-05-23/07-03-34
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choices:
|
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hparams: hparams
|
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model: pythia_diamonds
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hydra/env: default
|
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hydra/callbacks: null
|
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hydra/job_logging: default
|
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hydra/hydra_logging: default
|
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hydra/hydra_help: default
|
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hydra/help: default
|
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hydra/sweeper: basic
|
164 |
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hydra/launcher: local
|
165 |
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hydra/output: default
|
166 |
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verbose: false
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.hydra/overrides.yaml
ADDED
@@ -0,0 +1 @@
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- push_to_hub=true
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README.md
CHANGED
@@ -1,199 +1,74 @@
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---
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tags:
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---
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-
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-
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-
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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-
- **Model type:** [More Information Needed]
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24 |
-
- **Language(s) (NLP):** [More Information Needed]
|
25 |
-
- **License:** [More Information Needed]
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-
- **Finetuned from model [optional]:** [More Information Needed]
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-
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-
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### Direct Use
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-
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-
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-
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-
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
|
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-
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### Out-of-Scope Use
|
53 |
-
|
54 |
-
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
|
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-
|
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## Bias, Risks, and Limitations
|
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-
|
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-
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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|
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[More Information Needed]
|
63 |
-
|
64 |
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### Recommendations
|
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-
|
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-
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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-
|
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
-
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## How to Get Started with the Model
|
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Use the code below to get started with the model.
|
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[More Information Needed]
|
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-
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## Training Details
|
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-
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### Training Data
|
79 |
-
|
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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81 |
-
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[More Information Needed]
|
83 |
-
|
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### Training Procedure
|
85 |
-
|
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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-
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-
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#### Training Hyperparameters
|
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|
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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-
|
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#### Speeds, Sizes, Times [optional]
|
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-
|
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-
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[More Information Needed]
|
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-
|
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## Evaluation
|
104 |
-
|
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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108 |
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#### Testing Data
|
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<!-- This should link to a Dataset Card if possible. -->
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[More Information Needed]
|
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-
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#### Factors
|
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-
|
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
-
|
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-
[More Information Needed]
|
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-
|
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#### Metrics
|
122 |
-
|
123 |
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
-
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[More Information Needed]
|
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### Results
|
128 |
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[More Information Needed]
|
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-
|
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#### Summary
|
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|
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## Model Examination [optional]
|
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-
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<!-- Relevant interpretability work for the model goes here -->
|
138 |
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|
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[More Information Needed]
|
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-
|
141 |
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## Environmental Impact
|
142 |
-
|
143 |
-
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
-
|
145 |
-
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
-
|
147 |
-
- **Hardware Type:** [More Information Needed]
|
148 |
-
- **Hours used:** [More Information Needed]
|
149 |
-
- **Cloud Provider:** [More Information Needed]
|
150 |
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- **Compute Region:** [More Information Needed]
|
151 |
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- **Carbon Emitted:** [More Information Needed]
|
152 |
-
|
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## Technical Specifications [optional]
|
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### Model Architecture and Objective
|
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[More Information Needed]
|
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### Compute Infrastructure
|
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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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## Citation [optional]
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-
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
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-
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**BibTeX:**
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-
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[More Information Needed]
|
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**APA:**
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[More Information Needed]
|
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## Glossary [optional]
|
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-
|
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<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
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[More Information Needed]
|
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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[More Information Needed]
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## Model Card Contact
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[More Information Needed]
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|
1 |
---
|
2 |
+
base_model: EleutherAI/pythia-14m
|
3 |
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tags:
|
4 |
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- generated_from_trainer
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5 |
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metrics:
|
6 |
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- accuracy
|
7 |
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model-index:
|
8 |
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- name: pythia-14m-measurement_pred
|
9 |
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results: []
|
10 |
---
|
11 |
|
12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
13 |
+
should probably proofread and complete it, then remove this comment. -->
|
14 |
|
15 |
+
# pythia-14m-measurement_pred
|
16 |
|
17 |
+
This model is a fine-tuned version of [EleutherAI/pythia-14m](https://huggingface.co/EleutherAI/pythia-14m) on an unknown dataset.
|
18 |
+
It achieves the following results on the evaluation set:
|
19 |
+
- Loss: 3.4923
|
20 |
+
- Accuracy: 0.25
|
21 |
+
- Accuracy Sensor 0: 1.0
|
22 |
+
- Auroc Sensor 0: 0.0
|
23 |
+
- Accuracy Sensor 1: 0.0
|
24 |
+
- Auroc Sensor 1: 0.0
|
25 |
+
- Accuracy Sensor 2: 0.0
|
26 |
+
- Auroc Sensor 2: 0.0
|
27 |
+
- Accuracy Aggregated: 0.0
|
28 |
+
- Auroc Aggregated: 0.0
|
29 |
|
30 |
+
## Model description
|
31 |
|
32 |
+
More information needed
|
33 |
|
34 |
+
## Intended uses & limitations
|
35 |
|
36 |
+
More information needed
|
37 |
|
38 |
+
## Training and evaluation data
|
39 |
|
40 |
+
More information needed
|
|
|
|
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|
|
41 |
|
42 |
+
## Training procedure
|
43 |
|
44 |
+
### Training hyperparameters
|
45 |
|
46 |
+
The following hyperparameters were used during training:
|
47 |
+
- learning_rate: 2e-05
|
48 |
+
- train_batch_size: 8
|
49 |
+
- eval_batch_size: 8
|
50 |
+
- seed: 42
|
51 |
+
- gradient_accumulation_steps: 32
|
52 |
+
- total_train_batch_size: 256
|
53 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
54 |
+
- lr_scheduler_type: cosine
|
55 |
+
- lr_scheduler_warmup_steps: 64
|
56 |
+
- num_epochs: 5
|
57 |
|
58 |
+
### Training results
|
59 |
|
60 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Accuracy Sensor 0 | Auroc Sensor 0 | Accuracy Sensor 1 | Auroc Sensor 1 | Accuracy Sensor 2 | Auroc Sensor 2 | Accuracy Aggregated | Auroc Aggregated |
|
61 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:--------------:|:-----------------:|:--------------:|:-----------------:|:--------------:|:-------------------:|:----------------:|
|
62 |
+
| No log | 1.0 | 1 | 3.7439 | 0.25 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
|
63 |
+
| No log | 2.0 | 2 | 3.7212 | 0.25 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
|
64 |
+
| No log | 3.0 | 3 | 3.6754 | 0.25 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
|
65 |
+
| No log | 4.0 | 4 | 3.6005 | 0.25 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
|
66 |
+
| No log | 5.0 | 5 | 3.4923 | 0.25 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
|
67 |
|
|
|
68 |
|
69 |
+
### Framework versions
|
70 |
|
71 |
+
- Transformers 4.41.0
|
72 |
+
- Pytorch 2.3.0+cu121
|
73 |
+
- Datasets 2.19.1
|
74 |
+
- Tokenizers 0.19.1
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"model_max_length": 1000000000000000019884624838656,
|
211 |
+
"pad_token": "<|endoftext|>",
|
212 |
+
"padding_side": "left",
|
213 |
+
"tokenizer_class": "GPTNeoXTokenizer",
|
214 |
+
"truncation_side": "left",
|
215 |
+
"unk_token": "<|endoftext|>"
|
216 |
+
}
|
train.log
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
[2024-05-23 07:03:37,995][accelerate.utils.other][WARNING] - Detected kernel version 5.4.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.
|
training_args.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:b28ebb80c1710831c7902d22068401883815c3a96b6d25ea485073c67d6a1d58
|
3 |
+
size 5112
|