transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:Samuael/asr-amharic-phoneme-based-37-5 license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: Samuael/asr-amharic-phoneme-based-37-5
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: asr-amharic-phoneme-based-37-5
  results: []
---

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# asr-amharic-phoneme-based-37-5

This model is a fine-tuned version of [Samuael/asr-amharic-phoneme-based-37-5](https://huggingface.co/Samuael/asr-amharic-phoneme-based-37-5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2362
- Wer: 0.3159
- Phoneme Cer: 0.0591
- Cer: 0.0858

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Phoneme Cer | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:------:|
| 0.0861        | 0.59  | 200  | 0.3128          | 0.3362 | 0.0633      | 0.0924 |
| 0.1616        | 1.18  | 400  | 0.2772          | 0.3354 | 0.0626      | 0.0910 |
| 0.1407        | 1.76  | 600  | 0.2752          | 0.3362 | 0.0631      | 0.0921 |
| 0.1267        | 2.35  | 800  | 0.2659          | 0.3367 | 0.0629      | 0.0912 |
| 0.1042        | 2.94  | 1000 | 0.2607          | 0.3338 | 0.0623      | 0.0905 |
| 0.1487        | 3.53  | 1200 | 0.2612          | 0.3255 | 0.0614      | 0.0899 |
| 0.09          | 4.12  | 1400 | 0.2679          | 0.3297 | 0.0623      | 0.0899 |
| 0.1001        | 4.71  | 1600 | 0.2655          | 0.3239 | 0.0607      | 0.0883 |
| 0.0863        | 5.29  | 1800 | 0.2723          | 0.3234 | 0.0608      | 0.0881 |
| 0.1198        | 5.88  | 2000 | 0.2530          | 0.3273 | 0.0608      | 0.0885 |
| 0.23          | 6.47  | 2200 | 0.2576          | 0.3273 | 0.0613      | 0.0892 |
| 0.1518        | 7.06  | 2400 | 0.2565          | 0.3191 | 0.0604      | 0.0874 |
| 0.2198        | 7.65  | 2600 | 0.2539          | 0.3134 | 0.0590      | 0.0858 |
| 0.1592        | 8.24  | 2800 | 0.2499          | 0.3174 | 0.0595      | 0.0863 |
| 0.1395        | 8.82  | 3000 | 0.2423          | 0.3190 | 0.0598      | 0.0865 |
| 0.163         | 9.41  | 3200 | 0.2401          | 0.3171 | 0.0590      | 0.0858 |
| 0.1252        | 10.0  | 3400 | 0.2362          | 0.3159 | 0.0591      | 0.0858 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
