t_5_classifier
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5350
- F1: 0.7367
- Accuracy: 0.7299
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: 2e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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 | F1 | Accuracy |
|---|---|---|---|---|---|
| No log | 1.0 | 49 | 0.6857 | 0.6233 | 0.4126 |
| No log | 2.0 | 98 | 0.6695 | 0.6567 | 0.5429 |
| No log | 3.0 | 147 | 0.6445 | 0.6898 | 0.6202 |
| No log | 4.0 | 196 | 0.6087 | 0.7053 | 0.6680 |
| No log | 5.0 | 245 | 0.5762 | 0.7122 | 0.6944 |
| No log | 6.0 | 294 | 0.5601 | 0.7180 | 0.7054 |
| No log | 7.0 | 343 | 0.5512 | 0.7281 | 0.7189 |
| No log | 8.0 | 392 | 0.5471 | 0.7303 | 0.7189 |
| No log | 9.0 | 441 | 0.5457 | 0.7311 | 0.7195 |
| No log | 10.0 | 490 | 0.5405 | 0.7315 | 0.7234 |
| 0.607 | 11.0 | 539 | 0.5386 | 0.7319 | 0.7234 |
| 0.607 | 12.0 | 588 | 0.5391 | 0.7321 | 0.7240 |
| 0.607 | 13.0 | 637 | 0.5378 | 0.7357 | 0.7286 |
| 0.607 | 14.0 | 686 | 0.5362 | 0.7368 | 0.7305 |
| 0.607 | 15.0 | 735 | 0.5352 | 0.7392 | 0.7324 |
| 0.607 | 16.0 | 784 | 0.5360 | 0.7344 | 0.7292 |
| 0.607 | 17.0 | 833 | 0.5360 | 0.7358 | 0.7292 |
| 0.607 | 18.0 | 882 | 0.5353 | 0.7359 | 0.7305 |
| 0.607 | 19.0 | 931 | 0.5351 | 0.7374 | 0.7305 |
| 0.607 | 20.0 | 980 | 0.5350 | 0.7367 | 0.7299 |
Framework versions
- Transformers 4.41.1
- Pytorch 1.13.1+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
google-t5/t5-small