| --- |
| license: apache-2.0 |
| base_model: t5-small |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: FingerFriend-t5-small |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # FingerFriend-t5-small |
|
|
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7464 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
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|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 1.6293 | 1.0 | 171 | 1.1671 | |
| | 1.195 | 2.0 | 342 | 1.0246 | |
| | 1.085 | 3.0 | 513 | 0.9553 | |
| | 1.0207 | 4.0 | 684 | 0.9096 | |
| | 0.9631 | 5.0 | 855 | 0.8782 | |
| | 0.9283 | 6.0 | 1026 | 0.8445 | |
| | 0.8987 | 7.0 | 1197 | 0.8352 | |
| | 0.8716 | 8.0 | 1368 | 0.8123 | |
| | 0.8556 | 9.0 | 1539 | 0.7983 | |
| | 0.8375 | 10.0 | 1710 | 0.7923 | |
| | 0.8239 | 11.0 | 1881 | 0.7757 | |
| | 0.8184 | 12.0 | 2052 | 0.7716 | |
| | 0.8053 | 13.0 | 2223 | 0.7642 | |
| | 0.7929 | 14.0 | 2394 | 0.7647 | |
| | 0.7867 | 15.0 | 2565 | 0.7597 | |
| | 0.7817 | 16.0 | 2736 | 0.7529 | |
| | 0.7751 | 17.0 | 2907 | 0.7506 | |
| | 0.7705 | 18.0 | 3078 | 0.7472 | |
| | 0.7657 | 19.0 | 3249 | 0.7467 | |
| | 0.7665 | 20.0 | 3420 | 0.7464 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.33.2 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.13.3 |
|
|
