chexagent-8b-instruct-trl-sft-ChartQA
This model is a fine-tuned version of StanfordAIMI/CheXagent-8b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2088
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: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 8
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.211 | 0.9999 | 3437 | 0.2192 |
| 0.2113 | 2.0 | 6875 | 0.2123 |
| 0.2069 | 2.9999 | 10312 | 0.2075 |
| 0.1995 | 4.0 | 13750 | 0.2108 |
| 0.2065 | 4.9999 | 17187 | 0.2112 |
| 0.192 | 6.0 | 20625 | 0.2070 |
| 0.2032 | 6.9999 | 24062 | 0.2104 |
| 0.1958 | 7.9988 | 27496 | 0.2088 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
StanfordAIMI/CheXagent-8b