---
library_name: transformers
base_model: Samuael/ethiopic-asr-characters
tags:
- generated_from_trainer
datasets:
- alffa_amharic
metrics:
- wer
model-index:
- name: ethiopic-asr-characters
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: alffa_amharic
      type: alffa_amharic
      config: clean
      split: None
      args: clean
    metrics:
    - name: Wer
      type: wer
      value: 0.29963354171157575
---

<!-- 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. -->

# ethiopic-asr-characters

This model is a fine-tuned version of [Samuael/ethiopic-asr-characters](https://huggingface.co/Samuael/ethiopic-asr-characters) on the alffa_amharic dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4428
- Wer: 0.2996
- Phoneme Cer: 0.1421

## 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: 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_steps: 100
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Phoneme Cer |
|:-------------:|:------:|:----:|:---------------:|:------:|:-----------:|
| 0.1559        | 0.2312 | 200  | 0.5540          | 0.3212 | 0.1475      |
| 0.1228        | 0.4624 | 400  | 0.5394          | 0.3142 | 0.1466      |
| 0.069         | 0.6936 | 600  | 0.5525          | 0.3139 | 0.1466      |
| 0.0997        | 0.9249 | 800  | 0.5531          | 0.3118 | 0.1462      |
| 0.0732        | 1.1561 | 1000 | 0.5644          | 0.3196 | 0.1465      |
| 0.1637        | 1.3873 | 1200 | 0.5367          | 0.3185 | 0.1468      |
| 0.1145        | 1.6185 | 1400 | 0.5215          | 0.3180 | 0.1468      |
| 0.1499        | 1.8497 | 1600 | 0.4985          | 0.3141 | 0.1455      |
| 0.1975        | 2.0809 | 1800 | 0.4814          | 0.3114 | 0.1446      |
| 0.2116        | 2.3121 | 2000 | 0.4855          | 0.3085 | 0.1446      |
| 0.2384        | 2.5434 | 2200 | 0.4702          | 0.3083 | 0.1441      |
| 0.4346        | 2.7746 | 2400 | 0.4762          | 0.3063 | 0.1435      |
| 0.3156        | 3.0058 | 2600 | 0.4677          | 0.3044 | 0.1432      |
| 0.5558        | 3.2370 | 2800 | 0.4574          | 0.2993 | 0.1425      |
| 0.2787        | 3.4682 | 3000 | 0.4478          | 0.2989 | 0.1420      |
| 0.3268        | 3.6994 | 3200 | 0.4466          | 0.2978 | 0.1418      |
| 0.3461        | 3.9306 | 3400 | 0.4428          | 0.2996 | 0.1421      |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3