Model save
Browse files- .gitattributes +1 -0
- README.md +53 -0
- config.json +32 -0
- generation_config.json +7 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +5 -0
- spiece.model +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +12 -0
- training_args.bin +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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base_model: google/mt5-small
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tags:
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- generated_from_trainer
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model-index:
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- name: PII_MT5_SMALL
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# PII_MT5_SMALL
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 64
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.2
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- num_epochs: 10
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### Training results
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 2.0.1
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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config.json
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{
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"_name_or_path": "google/mt5-small",
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"architectures": [
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"MT5ForConditionalGeneration"
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],
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"classifier_dropout": 0.0,
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"d_ff": 1024,
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"d_kv": 64,
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"d_model": 512,
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"decoder_start_token_id": 0,
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"dense_act_fn": "gelu_new",
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"dropout_rate": 0.1,
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"eos_token_id": 1,
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"feed_forward_proj": "gated-gelu",
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"is_gated_act": true,
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"layer_norm_epsilon": 1e-06,
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"model_type": "mt5",
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"num_decoder_layers": 8,
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"num_heads": 6,
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"num_layers": 8,
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"pad_token_id": 0,
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"relative_attention_max_distance": 128,
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"relative_attention_num_buckets": 32,
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"tie_word_embeddings": false,
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"tokenizer_class": "T5Tokenizer",
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"torch_dtype": "float32",
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"transformers_version": "4.32.1",
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"use_cache": true,
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"vocab_size": 250112
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}
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generation_config.json
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{
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"_from_model_config": true,
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"decoder_start_token_id": 0,
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"eos_token_id": 1,
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"pad_token_id": 0,
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"transformers_version": "4.32.1"
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}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:f2624b73e2e7a8bfa2a75fe80b29331a2ac7657082f6e4e7766fb574eef4e1c4
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size 1200772613
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special_tokens_map.json
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{
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"eos_token": "</s>",
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"pad_token": "<pad>",
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"unk_token": "<unk>"
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}
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spiece.model
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version https://git-lfs.github.com/spec/v1
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size 4309802
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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size 16330634
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tokenizer_config.json
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{
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"additional_special_tokens": null,
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"clean_up_tokenization_spaces": true,
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"eos_token": "</s>",
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"extra_ids": 0,
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"legacy": true,
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"model_max_length": 1000000000000000019884624838656,
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"pad_token": "<pad>",
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"sp_model_kwargs": {},
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"tokenizer_class": "T5Tokenizer",
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"unk_token": "<unk>"
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}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:8c62799c308ef14054e365731041dd154efd8bf1c35525ea9a5d6e5b3d1d5433
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size 4219
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