t-5_base_extractive_512_375
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2983
- Rouge1: 0.6512
- Rouge2: 0.3701
- Rougel: 0.5849
- Rougelsum: 0.585
- Wer: 0.5233
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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Wer |
---|---|---|---|---|---|---|---|---|
No log | 0.13 | 250 | 1.4099 | 0.6341 | 0.3466 | 0.5641 | 0.5641 | 0.5468 |
1.898 | 0.27 | 500 | 1.3537 | 0.6413 | 0.3565 | 0.5736 | 0.5737 | 0.5367 |
1.898 | 0.4 | 750 | 1.3306 | 0.645 | 0.3619 | 0.5779 | 0.578 | 0.5309 |
1.4411 | 0.53 | 1000 | 1.3141 | 0.6481 | 0.3659 | 0.581 | 0.5812 | 0.5275 |
1.4411 | 0.66 | 1250 | 1.3056 | 0.6502 | 0.3684 | 0.5833 | 0.5835 | 0.525 |
1.4014 | 0.8 | 1500 | 1.3004 | 0.6507 | 0.3694 | 0.5843 | 0.5845 | 0.5235 |
1.4014 | 0.93 | 1750 | 1.2983 | 0.6512 | 0.3701 | 0.5849 | 0.585 | 0.5233 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for jgibb/t-5_base_extractive_512_375
Base model
google-t5/t5-base