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:
- Loss: 2.5678
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
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Model tree for ahmedshark/mt5-small-finetuned-summarization
Base model
google/mt5-small