End of training
Browse files- .gitattributes +1 -0
- README.md +48 -0
- config.json +33 -0
- generation_config.json +7 -0
- model.safetensors +3 -0
- special_tokens_map.json +23 -0
- spiece.model +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +37 -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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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: bigscience/mt0-base
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tags:
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- generated_from_trainer
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model-index:
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- name: nana_vai_model2
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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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# nana_vai_model2
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This model is a fine-tuned version of [bigscience/mt0-base](https://huggingface.co/bigscience/mt0-base) on the None 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: 0.0001
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- train_batch_size: 2
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- eval_batch_size: 2
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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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- num_epochs: 5
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### Framework versions
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- Transformers 4.41.0
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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{
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"_name_or_path": "bigscience/mt0-base",
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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": 2048,
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"d_kv": 64,
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"d_model": 768,
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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": 12,
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"num_heads": 12,
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"num_layers": 12,
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"output_past": true,
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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": "4.41.0",
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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": "4.41.0"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:854a6141d2efebc2c808d5eb484a2ae087fbb9f6bd7f2974e6dcb1adc523b8f5
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size 2329638768
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special_tokens_map.json
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{
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"content": "</s>",
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"lstrip": false,
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"rstrip": false,
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"single_word": false
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"pad_token": {
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"unk_token": {
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"rstrip": false,
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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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oid sha256:602c1e95d301f568fb7d5b321b1036c9af2471f28fb422ed755544130664b0cd
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size 16315456
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tokenizer_config.json
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{
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"additional_special_tokens": [],
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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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"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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