trainer_output
This model is a fine-tuned version of on the arrow dataset. It achieves the following results on the evaluation set:
- Loss: 2.9122
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: 1337
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 1024
- total_eval_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- training_steps: 13794
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.4848 | 0.3625 | 5000 | 4.3929 |
2.9899 | 0.7249 | 10000 | 2.9122 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu126
- Datasets 2.21.0
- Tokenizers 0.21.1
- Downloads last month
- 38
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support