---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xlsr-am-adap-phon
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: am
      split: validation
      args: am
    metrics:
    - type: wer
      value: 0.9302421009437833
      name: Wer
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning-amharic/runs/4961bdc2)
# xlsr-am-adap-phon

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5869
- Wer: 0.9302
- Cer: 0.4393

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 6.6235        | 6.8966  | 100  | 6.3103          | 1.0    | 1.0    |
| 4.227         | 13.7931 | 200  | 4.2662          | 1.0    | 1.0    |
| 4.1461        | 20.6897 | 300  | 4.1543          | 1.0    | 0.9966 |
| 4.146         | 27.5862 | 400  | 4.1716          | 1.0    | 0.9859 |
| 4.105         | 34.4828 | 500  | 4.1391          | 1.0    | 0.9740 |
| 3.5688        | 41.3793 | 600  | 3.6625          | 1.0    | 0.9749 |
| 1.5705        | 48.2759 | 700  | 2.2315          | 1.0029 | 0.5187 |
| 0.6683        | 55.1724 | 800  | 2.2517          | 0.9684 | 0.4595 |
| 0.577         | 62.0690 | 900  | 2.2995          | 0.9528 | 0.4413 |
| 0.3109        | 68.9655 | 1000 | 2.4239          | 0.9397 | 0.4575 |
| 0.2803        | 75.8621 | 1100 | 2.4491          | 0.9508 | 0.4474 |
| 0.2136        | 82.7586 | 1200 | 2.4916          | 0.9179 | 0.4323 |
| 0.3282        | 89.6552 | 1300 | 2.5652          | 0.9302 | 0.4401 |
| 0.2118        | 96.5517 | 1400 | 2.5869          | 0.9302 | 0.4393 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1