RottenLemons
commited on
Commit
•
c29a4b4
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Parent(s):
aacf05b
End of training
Browse files- README.md +58 -0
- generation_config.json +6 -0
- logs/events.out.tfevents.1689374295.92a4a412ef7c.210.1 +2 -2
- logs/events.out.tfevents.1689385206.92a4a412ef7c.210.2 +3 -0
- special_tokens_map.json +107 -0
- spiece.model +3 -0
- tokenizer.json +0 -0
- tokenizer_config.json +112 -0
README.md
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---
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license: apache-2.0
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base_model: google/flan-t5-base
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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- name: flan-t5-base
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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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# flan-t5-base
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This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0055
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- F1: 99.5394
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- Gen Len: 2.2532
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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: 0.0003
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- train_batch_size: 8
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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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- num_epochs: 1
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### Training results
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 2.0.0
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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generation_config.json
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{
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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": "4.31.0.dev0"
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}
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logs/events.out.tfevents.1689374295.92a4a412ef7c.210.1
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size
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size 5558
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logs/events.out.tfevents.1689385206.92a4a412ef7c.210.2
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special_tokens_map.json
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spiece.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:d60acb128cf7b7f2536e8f38a5b18a05535c9e14c7a355904270e15b0945ea86
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size 791656
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tokenizer.json
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The diff for this file is too large to render.
See raw diff
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tokenizer_config.json
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{
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"tokenizer_class": "T5Tokenizer",
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"unk_token": "<unk>"
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}
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