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---
license: mit
tags:
- generated_from_trainer
base_model: facebook/w2v-bert-2.0
datasets:
- generator
metrics:
- wer
model-index:
- name: wav2vec2-bert-fon
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: generator
type: generator
config: default
split: train
args: default
metrics:
- type: wer
value: 0.13241653693132677
name: Wer
---
<!-- 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. -->
# wav2vec2-bert-fon
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1612
- Wer: 0.1324
## 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: 3e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 0.18 | 250 | 1.2212 | 0.8079 |
| 2.1756 | 0.35 | 500 | 0.6697 | 0.6058 |
| 2.1756 | 0.53 | 750 | 0.5137 | 0.4606 |
| 0.5041 | 0.7 | 1000 | 0.4337 | 0.4234 |
| 0.5041 | 0.88 | 1250 | 0.3452 | 0.3529 |
| 0.426 | 1.05 | 1500 | 0.2770 | 0.2910 |
| 0.426 | 1.23 | 1750 | 0.2681 | 0.2439 |
| 0.2916 | 1.4 | 2000 | 0.2423 | 0.2155 |
| 0.2916 | 1.58 | 2250 | 0.2342 | 0.2077 |
| 0.2591 | 1.75 | 2500 | 0.1986 | 0.1791 |
| 0.2591 | 1.93 | 2750 | 0.1864 | 0.1597 |
| 0.2261 | 2.1 | 3000 | 0.1712 | 0.1419 |
| 0.2261 | 2.28 | 3250 | 0.1786 | 0.1497 |
| 0.1564 | 2.45 | 3500 | 0.1612 | 0.1324 |
| 0.1564 | 2.63 | 3750 | 0.1730 | 0.1591 |
| 0.1542 | 2.8 | 4000 | 0.1558 | 0.1364 |
| 0.1542 | 2.98 | 4250 | 0.1493 | 0.1581 |
| 0.1559 | 3.15 | 4500 | 0.1489 | 0.1347 |
| 0.1559 | 3.33 | 4750 | 0.2036 | 0.1486 |
| 0.1992 | 3.5 | 5000 | 0.2644 | 0.1582 |
| 0.1992 | 3.68 | 5250 | 0.2401 | 0.1878 |
| 0.291 | 3.85 | 5500 | 0.2409 | 0.1749 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
|