transformers pytorch wav2vec2 automatic-speech-recognition generated_from_trainer base_model:nguyenminhly/base_phase3 license:cc-by-nc-4.0 endpoints_compatible region:us
---
license: cc-by-nc-4.0
base_model: nguyenminhly/base_phase3
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: base_phase4
  results: []
---

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# base_phase4

This model is a fine-tuned version of [nguyenminhly/base_phase3](https://huggingface.co/nguyenminhly/base_phase3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2538
- Wer: 0.1236

## 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: 16
- 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: 70

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 1.7336        | 4.49  | 2000  | 0.3028          | 0.1418 |
| 0.0887        | 8.99  | 4000  | 0.2627          | 0.1411 |
| 0.0679        | 13.48 | 6000  | 0.2520          | 0.1335 |
| 0.0644        | 17.98 | 8000  | 0.2663          | 0.1333 |
| 0.0555        | 22.47 | 10000 | 0.2783          | 0.1333 |
| 0.054         | 26.97 | 12000 | 0.2881          | 0.1360 |
| 0.0502        | 31.46 | 14000 | 0.3052          | 0.1340 |
| 0.0433        | 35.96 | 16000 | 0.2875          | 0.1317 |
| 0.0444        | 40.45 | 18000 | 0.2732          | 0.1319 |
| 0.0415        | 44.94 | 20000 | 0.2543          | 0.1303 |
| 0.0344        | 49.44 | 22000 | 0.2584          | 0.1275 |
| 0.0337        | 53.93 | 24000 | 0.2640          | 0.1273 |
| 0.0299        | 58.43 | 26000 | 0.2744          | 0.1271 |
| 0.0288        | 62.92 | 28000 | 0.2562          | 0.1252 |
| 0.0363        | 67.42 | 30000 | 0.2538          | 0.1236 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
