ghc-google-t5-v1_1-large-intra_model-sorted
This model is a fine-tuned version of google/t5-v1_1-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2695
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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 200
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
15.9581 | 1.0 | 345 | 15.6856 |
10.8736 | 2.0 | 690 | 11.4385 |
10.3765 | 3.0 | 1035 | 10.8459 |
3.15 | 4.0 | 1380 | 2.7128 |
0.2927 | 5.0 | 1725 | 0.2377 |
0.3245 | 6.0 | 2070 | 0.2290 |
0.3004 | 7.0 | 2415 | 0.2255 |
0.2514 | 8.0 | 2760 | 0.2242 |
0.2371 | 9.0 | 3105 | 0.2189 |
0.2359 | 10.0 | 3450 | 0.2122 |
0.2501 | 11.0 | 3795 | 0.2092 |
0.2344 | 12.0 | 4140 | 0.2053 |
0.2419 | 13.0 | 4485 | 0.2090 |
0.2542 | 14.0 | 4830 | 0.2080 |
0.227 | 15.0 | 5175 | 0.2079 |
0.2213 | 16.0 | 5520 | 0.2055 |
0.2104 | 17.0 | 5865 | 0.2066 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1
Model tree for owanr/ghc-google-t5-v1_1-large-intra_model-sorted-model_annots_str
Base model
google/t5-v1_1-large