|
--- |
|
license: other |
|
base_model: HuggingFaceM4/idefics-9b-instruct |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: idefics-9b-instruct-ft-instruct-compact |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# idefics-9b-instruct-ft-instruct-compact |
|
|
|
This model is a fine-tuned version of [HuggingFaceM4/idefics-9b-instruct](https://huggingface.co/HuggingFaceM4/idefics-9b-instruct) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5312 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 32 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 3 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 3.9471 | 0.18 | 25 | 3.9005 | |
|
| 3.513 | 0.36 | 50 | 3.4236 | |
|
| 2.8952 | 0.54 | 75 | 2.5822 | |
|
| 1.9127 | 0.73 | 100 | 1.7289 | |
|
| 1.2521 | 0.91 | 125 | 1.0073 | |
|
| 0.7576 | 1.09 | 150 | 0.7103 | |
|
| 0.6537 | 1.27 | 175 | 0.6171 | |
|
| 0.5969 | 1.45 | 200 | 0.5845 | |
|
| 0.5778 | 1.63 | 225 | 0.5681 | |
|
| 0.5663 | 1.82 | 250 | 0.5559 | |
|
| 0.558 | 2.0 | 275 | 0.5471 | |
|
| 0.5595 | 2.18 | 300 | 0.5409 | |
|
| 0.5417 | 2.36 | 325 | 0.5367 | |
|
| 0.5422 | 2.54 | 350 | 0.5341 | |
|
| 0.54 | 2.72 | 375 | 0.5321 | |
|
| 0.5474 | 2.91 | 400 | 0.5312 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.0.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|