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---
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v2-base-pretrained_lr5e-5_at0.7_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_at0.7_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: 1.8380
- Wer: 0.1653
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 18.7456 | 4.46 | 250 | 4.0623 | 1.0 |
| 3.321 | 8.93 | 500 | 3.1987 | 1.0 |
| 3.0779 | 13.39 | 750 | 3.0954 | 1.0 |
| 1.8257 | 17.86 | 1000 | 0.8216 | 0.6275 |
| 0.3449 | 22.32 | 1250 | 1.1757 | 0.3268 |
| 0.2036 | 26.79 | 1500 | 1.2369 | 0.1982 |
| 0.1299 | 31.25 | 1750 | 1.1629 | 0.1991 |
| 0.0998 | 35.71 | 2000 | 1.3491 | 0.1743 |
| 0.0772 | 40.18 | 2250 | 1.4032 | 0.1730 |
| 0.0667 | 44.64 | 2500 | 1.7240 | 0.1756 |
| 0.0558 | 49.11 | 2750 | 1.7005 | 0.1709 |
| 0.0488 | 53.57 | 3000 | 1.7088 | 0.1717 |
| 0.0427 | 58.04 | 3250 | 1.6884 | 0.1649 |
| 0.0389 | 62.5 | 3500 | 1.7467 | 0.1670 |
| 0.035 | 66.96 | 3750 | 1.8174 | 0.1653 |
| 0.0332 | 71.43 | 4000 | 1.8380 | 0.1653 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1
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