---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-Fleurs_AMMI_AFRIVOICE_LRSC-ln-20hrs-v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v-bert-2.0-Fleurs_AMMI_AFRIVOICE_LRSC-ln-20hrs-v2

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co./facebook/w2v-bert-2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7994
- Wer: 0.2042
- Cer: 0.0647

## 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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 80
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 2.2265        | 1.0   | 356   | 0.4952          | 0.3304 | 0.1008 |
| 0.5303        | 2.0   | 712   | 0.3928          | 0.2891 | 0.0862 |
| 0.4278        | 3.0   | 1068  | 0.3568          | 0.2574 | 0.0769 |
| 0.3675        | 4.0   | 1424  | 0.3322          | 0.2385 | 0.0735 |
| 0.3271        | 5.0   | 1780  | 0.3118          | 0.2411 | 0.0776 |
| 0.2848        | 6.0   | 2136  | 0.3208          | 0.2092 | 0.0659 |
| 0.2556        | 7.0   | 2492  | 0.3289          | 0.2090 | 0.0658 |
| 0.2265        | 8.0   | 2848  | 0.3280          | 0.2324 | 0.0812 |
| 0.2043        | 9.0   | 3204  | 0.3279          | 0.2206 | 0.0700 |
| 0.1865        | 10.0  | 3560  | 0.3551          | 0.2132 | 0.0676 |
| 0.1658        | 11.0  | 3916  | 0.3360          | 0.2108 | 0.0697 |
| 0.1521        | 12.0  | 4272  | 0.3539          | 0.2347 | 0.0785 |
| 0.1408        | 13.0  | 4628  | 0.3642          | 0.2124 | 0.0708 |
| 0.128         | 14.0  | 4984  | 0.3877          | 0.2141 | 0.0689 |
| 0.1159        | 15.0  | 5340  | 0.4239          | 0.1999 | 0.0635 |
| 0.1073        | 16.0  | 5696  | 0.4337          | 0.2142 | 0.0700 |
| 0.0975        | 17.0  | 6052  | 0.4401          | 0.2022 | 0.0653 |
| 0.0899        | 18.0  | 6408  | 0.4767          | 0.2101 | 0.0662 |
| 0.0857        | 19.0  | 6764  | 0.4927          | 0.2041 | 0.0677 |
| 0.0783        | 20.0  | 7120  | 0.5006          | 0.2091 | 0.0677 |
| 0.0714        | 21.0  | 7476  | 0.5030          | 0.2140 | 0.0709 |
| 0.0667        | 22.0  | 7832  | 0.5110          | 0.2144 | 0.0691 |
| 0.0665        | 23.0  | 8188  | 0.5129          | 0.2136 | 0.0669 |
| 0.0586        | 24.0  | 8544  | 0.5906          | 0.1980 | 0.0632 |
| 0.0527        | 25.0  | 8900  | 0.6139          | 0.2019 | 0.0631 |
| 0.0471        | 26.0  | 9256  | 0.5897          | 0.2127 | 0.0677 |
| 0.0425        | 27.0  | 9612  | 0.6123          | 0.2037 | 0.0655 |
| 0.0374        | 28.0  | 9968  | 0.5954          | 0.2154 | 0.0697 |
| 0.035         | 29.0  | 10324 | 0.6249          | 0.2017 | 0.0634 |
| 0.0311        | 30.0  | 10680 | 0.6401          | 0.2056 | 0.0649 |
| 0.0274        | 31.0  | 11036 | 0.6688          | 0.2105 | 0.0668 |
| 0.0243        | 32.0  | 11392 | 0.6783          | 0.2122 | 0.0661 |
| 0.0223        | 33.0  | 11748 | 0.6974          | 0.2062 | 0.0652 |
| 0.0188        | 34.0  | 12104 | 0.7393          | 0.2069 | 0.0662 |
| 0.0177        | 35.0  | 12460 | 0.7598          | 0.2065 | 0.0645 |
| 0.0168        | 36.0  | 12816 | 0.7584          | 0.2058 | 0.0640 |
| 0.0137        | 37.0  | 13172 | 0.8009          | 0.2052 | 0.0645 |
| 0.0122        | 38.0  | 13528 | 0.7671          | 0.2045 | 0.0644 |
| 0.0105        | 39.0  | 13884 | 0.7994          | 0.2042 | 0.0647 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3