|
--- |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- soda-clip-loader |
|
model-index: |
|
- name: soda-clip-finetuned |
|
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. --> |
|
|
|
# soda-clip-finetuned |
|
|
|
This model was trained from scratch on the soda-clip-loader dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.9564 |
|
|
|
## 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-05 |
|
- train_batch_size: 128 |
|
- eval_batch_size: 128 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 4.6533 | 0.15 | 100 | 4.5663 | |
|
| 4.5243 | 0.29 | 200 | 4.4131 | |
|
| 4.2506 | 0.44 | 300 | 3.9908 | |
|
| 3.9692 | 0.59 | 400 | 3.8105 | |
|
| 3.7576 | 0.74 | 500 | 3.6515 | |
|
| 3.5935 | 0.88 | 600 | 3.4758 | |
|
| 3.3874 | 1.03 | 700 | 3.3259 | |
|
| 3.1691 | 1.18 | 800 | 3.1645 | |
|
| 3.021 | 1.33 | 900 | 3.0139 | |
|
| 2.9045 | 1.47 | 1000 | 2.9027 | |
|
| 2.8391 | 1.62 | 1100 | 2.8245 | |
|
| 2.7293 | 1.77 | 1200 | 2.6703 | |
|
| 2.6177 | 1.92 | 1300 | 2.5465 | |
|
| 2.3473 | 2.06 | 1400 | 2.5076 | |
|
| 2.1463 | 2.21 | 1500 | 2.4233 | |
|
| 2.0842 | 2.36 | 1600 | 2.3488 | |
|
| 2.0204 | 2.51 | 1700 | 2.2738 | |
|
| 2.0013 | 2.65 | 1800 | 2.2473 | |
|
| 1.9325 | 2.8 | 1900 | 2.2017 | |
|
| 1.9072 | 2.95 | 2000 | 2.1397 | |
|
| 1.5792 | 3.1 | 2100 | 2.1203 | |
|
| 1.3949 | 3.24 | 2200 | 2.0973 | |
|
| 1.3664 | 3.39 | 2300 | 2.0737 | |
|
| 1.3545 | 3.54 | 2400 | 2.0320 | |
|
| 1.3144 | 3.69 | 2500 | 2.0143 | |
|
| 1.2897 | 3.83 | 2600 | 1.9552 | |
|
| 1.2706 | 3.98 | 2700 | 1.9497 | |
|
| 0.9014 | 4.13 | 2800 | 1.9983 | |
|
| 0.8365 | 4.28 | 2900 | 1.9960 | |
|
| 0.8187 | 4.42 | 3000 | 1.9886 | |
|
| 0.8001 | 4.57 | 3100 | 1.9709 | |
|
| 0.7979 | 4.72 | 3200 | 1.9513 | |
|
| 0.7698 | 4.87 | 3300 | 1.9564 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.2.0+cu121 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.2 |
|
|
