File size: 2,248 Bytes
eb5decb 8d5bdf9 eb5decb be57eef eb5decb be57eef eb5decb |
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 77 |
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: models
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. -->
# models
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0169
- Wer: 0.2673
## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.6087 | 1.26 | 500 | 3.0092 | 1.0 |
| 2.1293 | 2.53 | 1000 | 0.4565 | 0.6872 |
| 0.443 | 3.79 | 1500 | 0.1887 | 0.3995 |
| 0.2368 | 5.05 | 2000 | 0.0564 | 0.3034 |
| 0.1775 | 6.31 | 2500 | 0.0398 | 0.2964 |
| 0.132 | 7.58 | 3000 | 0.0574 | 0.2895 |
| 0.1176 | 8.84 | 3500 | 0.0298 | 0.2749 |
| 0.1023 | 10.1 | 4000 | 0.0243 | 0.2708 |
| 0.0833 | 11.36 | 4500 | 0.0235 | 0.2796 |
| 0.0668 | 12.63 | 5000 | 0.0160 | 0.2714 |
| 0.0559 | 13.89 | 5500 | 0.0264 | 0.2749 |
| 0.0414 | 15.15 | 6000 | 0.0157 | 0.2673 |
| 0.0388 | 16.41 | 6500 | 0.0231 | 0.2772 |
| 0.0313 | 17.68 | 7000 | 0.0168 | 0.2667 |
| 0.0286 | 18.94 | 7500 | 0.0169 | 0.2673 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|