---
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: 0.3836
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 23.2159       | 0.6   | 100  | 22.1148         | 1   |
| 18.1848       | 1.2   | 200  | 16.7223         | 1   |
| 9.7817        | 1.8   | 300  | 7.9404          | 1   |
| 4.5091        | 2.4   | 400  | 3.7900          | 1   |
| 3.4946        | 2.99  | 500  | 3.2953          | 1   |
| 3.3286        | 3.59  | 600  | 3.1827          | 1   |
| 3.2078        | 4.19  | 700  | 3.1068          | 1   |
| 3.1528        | 4.79  | 800  | 3.0573          | 1   |
| 3.0709        | 5.39  | 900  | 3.0196          | 1   |
| 3.0163        | 5.99  | 1000 | 2.9919          | 1   |
| 2.9789        | 6.59  | 1100 | 2.9504          | 1   |
| 2.9468        | 7.19  | 1200 | 2.9272          | 1   |
| 2.9389        | 7.78  | 1300 | 2.9129          | 1   |
| 2.9192        | 8.38  | 1400 | 2.9005          | 1   |
| 2.9069        | 8.98  | 1500 | 2.8861          | 1   |
| 2.9074        | 9.58  | 1600 | 2.8816          | 1   |
| 2.883         | 10.18 | 1700 | 2.8746          | 1   |
| 2.8746        | 10.78 | 1800 | 2.8718          | 1   |
| 2.8637        | 11.38 | 1900 | 2.8567          | 1   |
| 2.8613        | 11.98 | 2000 | 2.8570          | 1   |
| 2.8598        | 12.57 | 2100 | 2.8449          | 1   |
| 2.8357        | 13.17 | 2200 | 2.8393          | 1   |
| 2.8352        | 13.77 | 2300 | 2.8350          | 1   |
| 2.8178        | 14.37 | 2400 | 2.7879          | 1   |
| 2.5089        | 14.97 | 2500 | 2.3686          | 1   |
| 2.0826        | 15.57 | 2600 | 1.8915          | 1   |
| 1.6003        | 16.17 | 2700 | 1.3513          | 1   |
| 1.2925        | 16.77 | 2800 | 1.0568          | 1   |
| 1.0837        | 17.37 | 2900 | 0.8760          | 1   |
| 0.9333        | 17.96 | 3000 | 0.7588          | 1   |
| 0.8214        | 18.56 | 3100 | 0.6841          | 1   |
| 0.7302        | 19.16 | 3200 | 0.6099          | 1   |
| 0.6815        | 19.76 | 3300 | 0.5459          | 1   |
| 0.6548        | 20.36 | 3400 | 0.5087          | 1   |
| 0.569         | 20.96 | 3500 | 0.4853          | 1   |
| 0.5919        | 21.56 | 3600 | 0.4666          | 1   |
| 0.5306        | 22.16 | 3700 | 0.4508          | 1   |
| 0.5228        | 22.75 | 3800 | 0.4389          | 1   |
| 0.5263        | 23.35 | 3900 | 0.4287          | 1   |
| 0.4945        | 23.95 | 4000 | 0.4182          | 1   |
| 0.4809        | 24.55 | 4100 | 0.4122          | 1   |
| 0.4813        | 25.15 | 4200 | 0.4112          | 1   |
| 0.4664        | 25.75 | 4300 | 0.3972          | 1   |
| 0.455         | 26.35 | 4400 | 0.3950          | 1   |
| 0.4415        | 26.95 | 4500 | 0.3962          | 1   |
| 0.4399        | 27.54 | 4600 | 0.3930          | 1   |
| 0.4451        | 28.14 | 4700 | 0.3864          | 1   |
| 0.4343        | 28.74 | 4800 | 0.3867          | 1   |
| 0.4418        | 29.34 | 4900 | 0.3865          | 1   |
| 0.4223        | 29.94 | 5000 | 0.3836          | 1   |


### Framework versions

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