---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: assis
  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. -->

# assis

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: 0.3440
- Wer: 1

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 3000
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 16.8292       | 1.56  | 100  | 16.7197         | 1   |
| 15.1534       | 3.12  | 200  | 14.3410         | 1   |
| 10.7755       | 4.69  | 300  | 9.9820          | 1   |
| 6.4859        | 6.25  | 400  | 6.1913          | 1   |
| 4.0464        | 7.81  | 500  | 3.8280          | 1   |
| 3.3418        | 9.38  | 600  | 3.2733          | 1   |
| 3.217         | 10.94 | 700  | 3.1409          | 1   |
| 3.0927        | 12.5  | 800  | 3.0469          | 1   |
| 3.0235        | 14.06 | 900  | 3.0015          | 1   |
| 2.9902        | 15.62 | 1000 | 2.9748          | 1   |
| 2.945         | 17.19 | 1100 | 2.9550          | 1   |
| 2.9293        | 18.75 | 1200 | 2.9262          | 1   |
| 2.9139        | 20.31 | 1300 | 2.9230          | 1   |
| 2.9084        | 21.88 | 1400 | 2.9067          | 1   |
| 2.8941        | 23.44 | 1500 | 2.9077          | 1   |
| 2.8883        | 25.0  | 1600 | 2.8858          | 1   |
| 2.872         | 26.56 | 1700 | 2.8709          | 1   |
| 2.8641        | 28.12 | 1800 | 2.8587          | 1   |
| 2.8548        | 29.69 | 1900 | 2.8537          | 1   |
| 2.8396        | 31.25 | 2000 | 2.8371          | 1   |
| 2.7043        | 32.81 | 2100 | 2.6063          | 1   |
| 2.3905        | 34.38 | 2200 | 2.2233          | 1   |
| 1.9862        | 35.94 | 2300 | 1.7478          | 1   |
| 1.5463        | 37.5  | 2400 | 1.3176          | 1   |
| 1.218         | 39.06 | 2500 | 0.9948          | 1   |
| 0.9606        | 40.62 | 2600 | 0.7820          | 1   |
| 0.7923        | 42.19 | 2700 | 0.6577          | 1   |
| 0.6811        | 43.75 | 2800 | 0.5650          | 1   |
| 0.5927        | 45.31 | 2900 | 0.5204          | 1   |
| 0.5449        | 46.88 | 3000 | 0.4857          | 1   |
| 0.4876        | 48.44 | 3100 | 0.4526          | 1   |
| 0.4646        | 50.0  | 3200 | 0.4281          | 1   |
| 0.4374        | 51.56 | 3300 | 0.4376          | 1   |
| 0.3952        | 53.12 | 3400 | 0.4075          | 1   |
| 0.3952        | 54.69 | 3500 | 0.3937          | 1   |
| 0.3558        | 56.25 | 3600 | 0.3875          | 1   |
| 0.3527        | 57.81 | 3700 | 0.3775          | 1   |
| 0.3349        | 59.38 | 3800 | 0.3701          | 1   |
| 0.3264        | 60.94 | 3900 | 0.3576          | 1   |
| 0.3108        | 62.5  | 4000 | 0.3644          | 1   |
| 0.3104        | 64.06 | 4100 | 0.3548          | 1   |
| 0.3012        | 65.62 | 4200 | 0.3510          | 1   |
| 0.3027        | 67.19 | 4300 | 0.3486          | 1   |
| 0.2967        | 68.75 | 4400 | 0.3431          | 1   |
| 0.2892        | 70.31 | 4500 | 0.3391          | 1   |
| 0.296         | 71.88 | 4600 | 0.3427          | 1   |
| 0.2821        | 73.44 | 4700 | 0.3469          | 1   |
| 0.2701        | 75.0  | 4800 | 0.3428          | 1   |
| 0.2825        | 76.56 | 4900 | 0.3426          | 1   |
| 0.2549        | 78.12 | 5000 | 0.3440          | 1   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3