| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - xsum |
| model-index: |
| - name: t5-small-xsum |
| 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. --> |
|
|
| # t5-small-xsum |
|
|
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 2.3953 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 1 |
| - eval_batch_size: 1 |
| - seed: 42 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 1 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:-----:|:---------------:| |
| | 2.8641 | 0.04 | 500 | 2.6202 | |
| | 2.7466 | 0.08 | 1000 | 2.5660 | |
| | 2.8767 | 0.12 | 1500 | 2.5319 | |
| | 2.7099 | 0.16 | 2000 | 2.5107 | |
| | 2.7752 | 0.2 | 2500 | 2.4922 | |
| | 2.6037 | 0.24 | 3000 | 2.4800 | |
| | 2.8236 | 0.27 | 3500 | 2.4677 | |
| | 2.7089 | 0.31 | 4000 | 2.4581 | |
| | 2.7299 | 0.35 | 4500 | 2.4498 | |
| | 2.7498 | 0.39 | 5000 | 2.4420 | |
| | 2.6186 | 0.43 | 5500 | 2.4346 | |
| | 2.7817 | 0.47 | 6000 | 2.4288 | |
| | 2.5559 | 0.51 | 6500 | 2.4239 | |
| | 2.6725 | 0.55 | 7000 | 2.4186 | |
| | 2.6316 | 0.59 | 7500 | 2.4149 | |
| | 2.5561 | 0.63 | 8000 | 2.4115 | |
| | 2.5708 | 0.67 | 8500 | 2.4097 | |
| | 2.5861 | 0.71 | 9000 | 2.4052 | |
| | 2.6363 | 0.74 | 9500 | 2.4024 | |
| | 2.7435 | 0.78 | 10000 | 2.4003 | |
| | 2.7258 | 0.82 | 10500 | 2.3992 | |
| | 2.6113 | 0.86 | 11000 | 2.3983 | |
| | 2.6006 | 0.9 | 11500 | 2.3972 | |
| | 2.5684 | 0.94 | 12000 | 2.3960 | |
| | 2.6181 | 0.98 | 12500 | 2.3953 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.18.0 |
| - Pytorch 1.10.0+cu111 |
| - Datasets 2.0.0 |
| - Tokenizers 0.11.6 |
|
|
