File size: 2,308 Bytes
ac407b0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 |
---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilhubert-finetuned-pulse
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. -->
# distilhubert-finetuned-pulse
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6143
- Accuracy: 0.7143
## 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: 4
- eval_batch_size: 4
- seed: 42
- 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_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6972 | 1.0 | 31 | 0.6880 | 0.7143 |
| 0.703 | 2.0 | 62 | 0.6044 | 0.7143 |
| 0.6737 | 3.0 | 93 | 0.6217 | 0.7143 |
| 0.6756 | 4.0 | 124 | 0.6400 | 0.7143 |
| 0.6557 | 5.0 | 155 | 0.6213 | 0.7143 |
| 0.6778 | 6.0 | 186 | 0.6109 | 0.7143 |
| 0.6884 | 7.0 | 217 | 0.6415 | 0.7143 |
| 0.6364 | 8.0 | 248 | 0.6205 | 0.7143 |
| 0.6506 | 9.0 | 279 | 0.6171 | 0.7143 |
| 0.675 | 10.0 | 310 | 0.6139 | 0.7143 |
| 0.7018 | 11.0 | 341 | 0.6145 | 0.7143 |
| 0.6766 | 12.0 | 372 | 0.6099 | 0.7143 |
| 0.6493 | 13.0 | 403 | 0.6131 | 0.7143 |
| 0.6482 | 14.0 | 434 | 0.6138 | 0.7143 |
| 0.8036 | 15.0 | 465 | 0.6143 | 0.7143 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|