best-echelon-model
This model is a fine-tuned version of google/flan-t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2217
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2963 | 0.9627 | 200 | 0.3645 |
| 0.1886 | 1.9242 | 400 | 0.2526 |
| 0.1497 | 2.8857 | 600 | 0.2311 |
| 0.1383 | 3.8472 | 800 | 0.2511 |
| 0.1476 | 4.8087 | 1000 | 0.2393 |
| 0.1341 | 5.7702 | 1200 | 0.2286 |
| 0.1288 | 6.7316 | 1400 | 0.2195 |
| 0.1085 | 7.6931 | 1600 | 0.2217 |
Framework versions
- PEFT 0.17.1
- Transformers 4.56.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.0
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Base model
google/flan-t5-base