---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- automatic-speech-recognition
- CLEAR-Global/chichewa_34_34h
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-chichewa_34_34h
  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-chichewa_34_34h

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the CLEAR-GLOBAL/CHICHEWA_34_34H - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3084
- Wer: 0.3910
- Cer: 0.1127

## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 100000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
| 1.2884        | 1.8458  | 1000  | 1.3872          | 1.0113 | 0.3808 |
| 0.092         | 3.6907  | 2000  | 0.5229          | 0.5397 | 0.1527 |
| 0.0604        | 5.5355  | 3000  | 0.4211          | 0.4785 | 0.1347 |
| 0.2837        | 7.3804  | 4000  | 0.3645          | 0.4376 | 0.1248 |
| 0.0217        | 9.2253  | 5000  | 0.3404          | 0.4469 | 0.1232 |
| 0.0299        | 11.0702 | 6000  | 0.3288          | 0.4160 | 0.1173 |
| 0.0162        | 12.9160 | 7000  | 0.3320          | 0.3983 | 0.1139 |
| 0.0436        | 14.7608 | 8000  | 0.3125          | 0.3847 | 0.1099 |
| 0.0205        | 16.6057 | 9000  | 0.3084          | 0.3910 | 0.1126 |
| 0.0198        | 18.4506 | 10000 | 0.4008          | 0.4002 | 0.1135 |
| 0.0516        | 20.2955 | 11000 | 0.3086          | 0.3701 | 0.1075 |
| 0.0057        | 22.1404 | 12000 | 0.3458          | 0.3847 | 0.1114 |
| 0.0041        | 23.9861 | 13000 | 0.3829          | 0.3899 | 0.1137 |
| 0.0142        | 25.8310 | 14000 | 0.4180          | 0.4121 | 0.1168 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1