mt5-small-finetuned-summarization
This model is a fine-tuned version of google/mt5-small on an unknown dataset.
It achieves the following results on the evaluation set:
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 90
- num_epochs: 1
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
| 3.0615 |
0.128 |
100 |
3.1638 |
| 3.461 |
0.256 |
200 |
2.8180 |
| 3.2633 |
0.384 |
300 |
2.7739 |
| 3.2169 |
0.512 |
400 |
2.6986 |
| 3.1099 |
0.64 |
500 |
2.6516 |
| 3.1311 |
0.768 |
600 |
2.6042 |
| 3.0676 |
0.896 |
700 |
2.5785 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
