pytorch tensorboard wav2vec2 automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-base-ft-cv3-v3
  results: []
---

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# wav2vec2-base-ft-cv3-v3

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the "mozilla-foundation/common_voice_3_0 english" dataset: "train" and "validation" splits are used for training while "test" split is used for validation.
It achieves the following results on the evaluation set:
- Loss: 0.5787
- Wer: 0.2470

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.5935        | 0.1   | 500   | 3.0085          | 1.0    |
| 1.6296        | 0.21  | 1000  | 1.0879          | 0.5895 |
| 0.7154        | 0.31  | 1500  | 0.8224          | 0.4839 |
| 0.6387        | 0.42  | 2000  | 0.7290          | 0.4302 |
| 0.5322        | 0.52  | 2500  | 0.6864          | 0.4044 |
| 0.497         | 0.63  | 3000  | 0.6294          | 0.3746 |
| 0.4659        | 0.73  | 3500  | 0.6388          | 0.3745 |
| 0.4452        | 0.84  | 4000  | 0.6122          | 0.3570 |
| 0.4356        | 0.94  | 4500  | 0.5770          | 0.3443 |
| 0.3976        | 1.05  | 5000  | 0.6145          | 0.3296 |
| 0.3767        | 1.15  | 5500  | 0.6099          | 0.3325 |
| 0.3704        | 1.25  | 6000  | 0.5998          | 0.3263 |
| 0.3541        | 1.36  | 6500  | 0.6070          | 0.3250 |
| 0.3592        | 1.46  | 7000  | 0.6076          | 0.3352 |
| 0.3508        | 1.57  | 7500  | 0.5712          | 0.3239 |
| 0.3437        | 1.67  | 8000  | 0.5729          | 0.3202 |
| 0.352         | 1.78  | 8500  | 0.5465          | 0.3100 |
| 0.34          | 1.88  | 9000  | 0.5418          | 0.3059 |
| 0.4086        | 1.99  | 9500  | 0.5189          | 0.3053 |
| 0.2968        | 2.09  | 10000 | 0.5373          | 0.3076 |
| 0.2968        | 2.2   | 10500 | 0.5602          | 0.3061 |
| 0.2956        | 2.3   | 11000 | 0.5651          | 0.3051 |
| 0.2863        | 2.41  | 11500 | 0.5476          | 0.2982 |
| 0.2852        | 2.51  | 12000 | 0.5579          | 0.2954 |
| 0.292         | 2.61  | 12500 | 0.5451          | 0.2953 |
| 0.2877        | 2.72  | 13000 | 0.5468          | 0.2905 |
| 0.285         | 2.82  | 13500 | 0.5283          | 0.2908 |
| 0.2872        | 2.93  | 14000 | 0.5240          | 0.2867 |
| 0.3286        | 3.03  | 14500 | 0.5078          | 0.2846 |
| 0.2526        | 3.14  | 15000 | 0.5373          | 0.2836 |
| 0.2494        | 3.24  | 15500 | 0.5566          | 0.2861 |
| 0.2534        | 3.35  | 16000 | 0.5378          | 0.2859 |
| 0.2435        | 3.45  | 16500 | 0.5225          | 0.2813 |
| 0.3144        | 3.56  | 17000 | 0.5203          | 0.2808 |
| 0.2501        | 3.66  | 17500 | 0.5176          | 0.2785 |
| 0.2469        | 3.76  | 18000 | 0.5022          | 0.2795 |
| 0.242         | 3.87  | 18500 | 0.5228          | 0.2757 |
| 0.242         | 3.97  | 19000 | 0.5024          | 0.2788 |
| 0.2205        | 4.08  | 19500 | 0.5318          | 0.2729 |
| 0.2149        | 4.18  | 20000 | 0.5492          | 0.2763 |
| 0.2186        | 4.29  | 20500 | 0.5599          | 0.2769 |
| 0.2191        | 4.39  | 21000 | 0.5493          | 0.2695 |
| 0.218         | 4.5   | 21500 | 0.5385          | 0.2709 |
| 0.2046        | 4.6   | 22000 | 0.5326          | 0.2718 |
| 0.2064        | 4.71  | 22500 | 0.5591          | 0.2725 |
| 0.2066        | 4.81  | 23000 | 0.5283          | 0.2700 |
| 0.2102        | 4.92  | 23500 | 0.5456          | 0.2713 |
| 0.3345        | 5.02  | 24000 | 0.5474          | 0.2698 |
| 0.1891        | 5.12  | 24500 | 0.5466          | 0.2672 |
| 0.1954        | 5.23  | 25000 | 0.5691          | 0.2731 |
| 0.1971        | 5.33  | 25500 | 0.5595          | 0.2741 |
| 0.1995        | 5.44  | 26000 | 0.5609          | 0.2716 |
| 0.1911        | 5.54  | 26500 | 0.5513          | 0.2684 |
| 0.1954        | 5.65  | 27000 | 0.5282          | 0.2683 |
| 0.193         | 5.75  | 27500 | 0.5460          | 0.2644 |
| 0.1974        | 5.86  | 28000 | 0.5415          | 0.2650 |
| 0.1947        | 5.96  | 28500 | 0.5227          | 0.2656 |
| 0.1836        | 6.07  | 29000 | 0.5361          | 0.2743 |
| 0.1741        | 6.17  | 29500 | 0.5637          | 0.2649 |
| 0.1776        | 6.27  | 30000 | 0.5705          | 0.2680 |
| 0.1747        | 6.38  | 30500 | 0.5587          | 0.2667 |
| 0.1761        | 6.48  | 31000 | 0.5480          | 0.2683 |
| 0.1715        | 6.59  | 31500 | 0.5547          | 0.2627 |
| 0.2424        | 6.69  | 32000 | 0.5254          | 0.2610 |
| 0.1756        | 6.8   | 32500 | 0.5301          | 0.2633 |
| 0.1761        | 6.9   | 33000 | 0.5267          | 0.2658 |
| 0.1751        | 7.01  | 33500 | 0.5611          | 0.2677 |
| 0.1653        | 7.11  | 34000 | 0.5617          | 0.2663 |
| 0.1591        | 7.22  | 34500 | 0.5435          | 0.2642 |
| 0.1559        | 7.32  | 35000 | 0.5608          | 0.2611 |
| 0.1604        | 7.43  | 35500 | 0.5477          | 0.2611 |
| 0.162         | 7.53  | 36000 | 0.5257          | 0.2559 |
| 0.1579        | 7.63  | 36500 | 0.5398          | 0.2570 |
| 0.162         | 7.74  | 37000 | 0.5566          | 0.2605 |
| 0.2351        | 7.84  | 37500 | 0.5371          | 0.2564 |
| 0.1566        | 7.95  | 38000 | 0.5507          | 0.2565 |
| 0.1515        | 8.05  | 38500 | 0.5640          | 0.2544 |
| 0.1459        | 8.16  | 39000 | 0.5739          | 0.2523 |
| 0.1463        | 8.26  | 39500 | 0.5596          | 0.2522 |
| 0.1466        | 8.37  | 40000 | 0.5522          | 0.2537 |
| 0.2372        | 8.47  | 40500 | 0.5567          | 0.2520 |
| 0.1488        | 8.58  | 41000 | 0.5546          | 0.2506 |
| 0.1492        | 8.68  | 41500 | 0.5533          | 0.2518 |
| 0.1454        | 8.78  | 42000 | 0.5488          | 0.2508 |
| 0.148         | 8.89  | 42500 | 0.5635          | 0.2526 |
| 0.1424        | 8.99  | 43000 | 0.5513          | 0.2509 |
| 0.1356        | 9.1   | 43500 | 0.5534          | 0.2527 |
| 0.1346        | 9.2   | 44000 | 0.5735          | 0.2497 |
| 0.1346        | 9.31  | 44500 | 0.5710          | 0.2489 |
| 0.1401        | 9.41  | 45000 | 0.5561          | 0.2491 |
| 0.2212        | 9.52  | 45500 | 0.5564          | 0.2482 |
| 0.1369        | 9.62  | 46000 | 0.5658          | 0.2484 |
| 0.1323        | 9.73  | 46500 | 0.5582          | 0.2495 |
| 0.1369        | 9.83  | 47000 | 0.5560          | 0.2503 |
| 0.1368        | 9.94  | 47500 | 0.5552          | 0.2489 |
| 0.1333        | 10.04 | 48000 | 0.5953          | 0.2491 |
| 0.1305        | 10.14 | 48500 | 0.5818          | 0.2520 |
| 0.1316        | 10.25 | 49000 | 0.5773          | 0.2506 |
| 0.1334        | 10.35 | 49500 | 0.5882          | 0.2485 |
| 0.1351        | 10.46 | 50000 | 0.5750          | 0.2483 |
| 0.1337        | 10.56 | 50500 | 0.5910          | 0.2486 |
| 0.2241        | 10.67 | 51000 | 0.5732          | 0.2491 |
| 0.1327        | 10.77 | 51500 | 0.5839          | 0.2493 |
| 0.1364        | 10.88 | 52000 | 0.5724          | 0.2464 |
| 0.1305        | 10.98 | 52500 | 0.5758          | 0.2468 |
| 0.128         | 11.09 | 53000 | 0.5811          | 0.2482 |
| 0.1267        | 11.19 | 53500 | 0.5903          | 0.2483 |
| 0.1262        | 11.29 | 54000 | 0.5792          | 0.2483 |
| 0.1291        | 11.4  | 54500 | 0.5735          | 0.2497 |
| 0.1228        | 11.5  | 55000 | 0.5920          | 0.2494 |
| 0.1249        | 11.61 | 55500 | 0.5907          | 0.2488 |
| 0.1266        | 11.71 | 56000 | 0.5786          | 0.2486 |
| 0.1235        | 11.82 | 56500 | 0.5790          | 0.2473 |
| 0.1243        | 11.92 | 57000 | 0.5787          | 0.2470 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.0
- Tokenizers 0.12.1
