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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_lr1e-4_at0.8_da0.1
  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_lr1e-4_at0.8_da0.1

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: 17.4872
- Wer: 1.0

## 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: 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: 3500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 37.4028       | 50.0  | 250  | 20.8788         | 1.0 |
| 15.6492       | 100.0 | 500  | 19.7127         | 1.0 |
| 16.1334       | 150.0 | 750  | 20.9635         | 1.0 |
| 20.9127       | 200.0 | 1000 | 17.5870         | 1.0 |
| 18.6712       | 250.0 | 1250 | 17.4758         | 1.0 |
| 18.5148       | 300.0 | 1500 | 17.4736         | 1.0 |
| 18.4769       | 350.0 | 1750 | 17.4742         | 1.0 |
| 18.5946       | 400.0 | 2000 | 17.5825         | 1.0 |
| 18.4632       | 450.0 | 2250 | 17.4559         | 1.0 |
| 18.3947       | 500.0 | 2500 | 17.4270         | 1.0 |
| 18.573        | 550.0 | 2750 | 17.5461         | 1.0 |
| 18.4756       | 600.0 | 3000 | 17.5971         | 1.0 |
| 18.4707       | 650.0 | 3250 | 17.5327         | 1.0 |
| 18.5019       | 700.0 | 3500 | 17.4872         | 1.0 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.14.6
- Tokenizers 0.14.1