t-5_base_experiment_1
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2275
- Rouge1: 0.6681
- Rouge2: 0.3985
- Rougel: 0.6063
- Rougelsum: 0.6063
- Wer: 0.4993
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 | 1.3344 | 0.6503 | 0.3757 | 0.5858 | 0.5858 | 0.5226 |
| 1.793 | 0.27 | 500 | 1.2824 | 0.6586 | 0.3854 | 0.5955 | 0.5955 | 0.5119 |
| 1.793 | 0.4 | 750 | 1.2598 | 0.6622 | 0.3915 | 0.5998 | 0.5998 | 0.5058 |
| 1.3637 | 0.53 | 1000 | 1.2439 | 0.6651 | 0.3943 | 0.6027 | 0.6027 | 0.5034 |
| 1.3637 | 0.66 | 1250 | 1.2370 | 0.6667 | 0.3967 | 0.6045 | 0.6045 | 0.5009 |
| 1.3241 | 0.8 | 1500 | 1.2305 | 0.6677 | 0.3981 | 0.6058 | 0.6059 | 0.4996 |
| 1.3241 | 0.93 | 1750 | 1.2275 | 0.6681 | 0.3985 | 0.6063 | 0.6063 | 0.4993 |
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_experiment_1
Base model
google-t5/t5-base