agenttuning_v1_tag4
This model is a fine-tuned version of Qwen/Qwen2.5-7B-Instruct on the agenttuning_v1_tag4 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3362
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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.3264 | 0.0860 | 100 | 0.4072 |
0.3504 | 0.1720 | 200 | 0.4065 |
0.526 | 0.2580 | 300 | 0.3899 |
0.5176 | 0.3439 | 400 | 0.3735 |
0.3618 | 0.4299 | 500 | 0.3685 |
0.4644 | 0.5159 | 600 | 0.3636 |
0.4007 | 0.6019 | 700 | 0.3495 |
0.2761 | 0.6879 | 800 | 0.3478 |
0.3908 | 0.7739 | 900 | 0.3378 |
0.4242 | 0.8598 | 1000 | 0.3422 |
0.3176 | 0.9458 | 1100 | 0.3362 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.7.1+cu126
- Datasets 3.1.0
- Tokenizers 0.20.3
- Downloads last month
- 11