---
license: apache-2.0
base_model: allenai/OLMo-7B
tags:
- generated_from_trainer
model-index:
- name: ollama-7B-Tinybook-epochs-1-lr-0002
results: []
---
[](https://github.com/OpenAccess-AI-Collective/axolotl)
See axolotl config
axolotl version: `0.4.0`
```yaml
base_model: allenai/OLMo-7B
tokenizer_type: AutoTokenizer
model_type: AutoModelForCausalLM
trust_remote_code: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: utrgvseniorproject/Tinybook
type: completion
dataset_prepared_path: /home/josegomez15/med-llm/last_run_prepared
val_set_size: 0.05
output_dir: ./ollama-7B-Tinybook-epochs-1-lr-0002
sequence_len: 4096
sample_packing: false
pad_to_sequence_len: true
wandb_project: olmo-7B-Tinybook
wandb_entity: utrgvmedai
wandb_watch:
wandb_name: olmo-7B-Tinybook-epochs-1-lr-0002
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 1
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: True # make sure you have this on True
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: false #olmo doesn't support
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
flash_attn_cross_entropy: false
flash_attn_rms_norm: true
flash_attn_fuse_qkv: false
flash_attn_fuse_mlp: true
warmup_steps: 100
evals_per_epoch: 4
eval_table_size:
eval_sample_packing:
saves_per_epoch: 1
debug:
deepspeed: /home/josegomez15/axolotl/deepspeed_configs/zero2.json
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:
```
# ollama-7B-Tinybook-epochs-1-lr-0002
This model is a fine-tuned version of [allenai/OLMo-7B](https://huggingface.co/allenai/OLMo-7B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3906
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.3047 | 0.33 | 1 | 2.4062 |
| 4.0859 | 0.67 | 2 | 2.3906 |
| 3.9805 | 1.0 | 3 | 2.3906 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.0