t5-small-samsum
This model is a fine-tuned version of google-t5/t5-small on an samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.6507
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 64
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 460 | 1.9598 |
| 2.4944 | 2.0 | 921 | 1.8661 |
| 2.0902 | 3.0 | 1381 | 1.8210 |
| 2.0173 | 4.0 | 1842 | 1.8009 |
| 1.9623 | 5.0 | 2302 | 1.7787 |
| 1.9331 | 6.0 | 2763 | 1.7637 |
| 1.903 | 7.0 | 3223 | 1.7514 |
| 1.881 | 8.0 | 3684 | 1.7390 |
| 1.8648 | 9.0 | 4144 | 1.7350 |
| 1.8463 | 10.0 | 4605 | 1.7242 |
| 1.8302 | 11.0 | 5065 | 1.7189 |
| 1.8119 | 12.0 | 5526 | 1.7098 |
| 1.8119 | 13.0 | 5986 | 1.7076 |
| 1.8007 | 14.0 | 6447 | 1.7057 |
| 1.7903 | 15.0 | 6907 | 1.6984 |
| 1.778 | 16.0 | 7368 | 1.6944 |
| 1.7639 | 17.0 | 7828 | 1.6907 |
| 1.7596 | 18.0 | 8289 | 1.6896 |
| 1.746 | 19.0 | 8749 | 1.6861 |
| 1.7342 | 20.0 | 9210 | 1.6860 |
| 1.732 | 21.0 | 9670 | 1.6808 |
| 1.719 | 22.0 | 10131 | 1.6760 |
| 1.7152 | 23.0 | 10591 | 1.6778 |
| 1.7082 | 24.0 | 11052 | 1.6762 |
| 1.7003 | 25.0 | 11512 | 1.6707 |
| 1.7003 | 26.0 | 11973 | 1.6722 |
| 1.6952 | 27.0 | 12433 | 1.6701 |
| 1.6848 | 28.0 | 12894 | 1.6671 |
| 1.6814 | 29.0 | 13354 | 1.6668 |
| 1.6743 | 30.0 | 13815 | 1.6637 |
| 1.6742 | 31.0 | 14275 | 1.6640 |
| 1.6652 | 32.0 | 14736 | 1.6624 |
| 1.6582 | 33.0 | 15196 | 1.6606 |
| 1.6575 | 34.0 | 15657 | 1.6605 |
| 1.6499 | 35.0 | 16117 | 1.6617 |
| 1.6455 | 36.0 | 16578 | 1.6601 |
| 1.6506 | 37.0 | 17038 | 1.6594 |
| 1.6506 | 38.0 | 17499 | 1.6556 |
| 1.637 | 39.0 | 17959 | 1.6570 |
| 1.6374 | 40.0 | 18420 | 1.6558 |
| 1.6303 | 41.0 | 18880 | 1.6557 |
| 1.6311 | 42.0 | 19341 | 1.6553 |
| 1.6234 | 43.0 | 19801 | 1.6570 |
| 1.619 | 44.0 | 20262 | 1.6537 |
| 1.6214 | 45.0 | 20722 | 1.6529 |
| 1.6183 | 46.0 | 21183 | 1.6542 |
| 1.609 | 47.0 | 21643 | 1.6543 |
| 1.6159 | 48.0 | 22104 | 1.6530 |
| 1.6101 | 49.0 | 22564 | 1.6524 |
| 1.6083 | 50.0 | 23025 | 1.6515 |
| 1.6083 | 51.0 | 23485 | 1.6528 |
| 1.605 | 52.0 | 23946 | 1.6526 |
| 1.6011 | 53.0 | 24406 | 1.6515 |
| 1.6028 | 54.0 | 24867 | 1.6517 |
| 1.6015 | 55.0 | 25327 | 1.6512 |
| 1.601 | 56.0 | 25788 | 1.6504 |
| 1.6007 | 57.0 | 26248 | 1.6513 |
| 1.5948 | 58.0 | 26709 | 1.6511 |
| 1.5973 | 59.0 | 27169 | 1.6515 |
| 1.5929 | 60.0 | 27630 | 1.6514 |
| 1.5955 | 61.0 | 28090 | 1.6507 |
| 1.5931 | 62.0 | 28551 | 1.6507 |
| 1.5939 | 63.0 | 29011 | 1.6507 |
| 1.5939 | 63.93 | 29440 | 1.6507 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 14
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for Prikshit7766/t5-small-samsum
Base model
google-t5/t5-small