File size: 2,368 Bytes
20c2b2e 9257fce 20c2b2e 9257fce 20c2b2e 9257fce 20c2b2e |
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 78 |
---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.2_da1
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. -->
# w2v2-base-pretrained_lr5e-5_at0.2_da1
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3038
- Wer: 0.1709
## 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: 32
- 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
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 19.5617 | 3.91 | 250 | 4.1984 | 1.0 |
| 3.3686 | 7.81 | 500 | 3.2319 | 1.0 |
| 3.1228 | 11.72 | 750 | 3.1341 | 1.0 |
| 2.9603 | 15.62 | 1000 | 2.3654 | 1.0 |
| 1.0738 | 19.53 | 1250 | 0.7578 | 0.5485 |
| 0.3549 | 23.44 | 1500 | 0.6579 | 0.2337 |
| 0.2219 | 27.34 | 1750 | 0.8304 | 0.1999 |
| 0.1579 | 31.25 | 2000 | 0.9428 | 0.1828 |
| 0.1216 | 35.16 | 2250 | 1.0046 | 0.1747 |
| 0.0958 | 39.06 | 2500 | 1.0114 | 0.1751 |
| 0.076 | 42.97 | 2750 | 1.2645 | 0.1768 |
| 0.0662 | 46.88 | 3000 | 1.2588 | 0.1739 |
| 0.0569 | 50.78 | 3250 | 1.3057 | 0.1730 |
| 0.0514 | 54.69 | 3500 | 1.2869 | 0.1696 |
| 0.0479 | 58.59 | 3750 | 1.2697 | 0.1704 |
| 0.0451 | 62.5 | 4000 | 1.3038 | 0.1709 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
|