transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:Samuael/asr-amharic-phoneme-based-37-4 license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: Samuael/asr-amharic-phoneme-based-37-4
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: asr-amharic-phoneme-based-37-4
  results: []
---

<!-- 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. -->

# asr-amharic-phoneme-based-37-4

This model is a fine-tuned version of [Samuael/asr-amharic-phoneme-based-37-4](https://huggingface.co/Samuael/asr-amharic-phoneme-based-37-4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2375
- Wer: 0.3633
- Phoneme Cer: 0.0675
- Cer: 0.1103

## 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: 5e-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: 30

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Phoneme Cer | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-----------:|:------:|
| 3.1066        | 0.59  | 200   | 3.2635          | 1.0    | 1.0         | 1.0    |
| 3.0018        | 1.18  | 400   | 3.2424          | 1.0    | 1.0         | 1.0    |
| 2.9877        | 1.76  | 600   | 3.0748          | 1.0    | 1.0         | 1.0    |
| 2.9609        | 2.35  | 800   | 3.0010          | 1.0    | 1.0         | 1.0    |
| 2.4744        | 2.94  | 1000  | 2.3659          | 1.0    | 0.9150      | 1.0000 |
| 1.221         | 3.53  | 1200  | 0.8924          | 0.8893 | 0.2290      | 0.3507 |
| 0.7713        | 4.12  | 1400  | 0.5988          | 0.6852 | 0.1544      | 0.2408 |
| 0.7683        | 4.71  | 1600  | 0.4776          | 0.6150 | 0.1299      | 0.2020 |
| 0.7059        | 5.29  | 1800  | 0.4349          | 0.5580 | 0.1164      | 0.1819 |
| 0.7168        | 5.88  | 2000  | 0.3947          | 0.5505 | 0.1106      | 0.1738 |
| 0.5871        | 6.47  | 2200  | 0.3703          | 0.5510 | 0.1078      | 0.1696 |
| 0.5302        | 7.06  | 2400  | 0.3443          | 0.5227 | 0.1015      | 0.1609 |
| 0.5622        | 7.65  | 2600  | 0.3325          | 0.4937 | 0.0967      | 0.1535 |
| 0.4664        | 8.24  | 2800  | 0.3216          | 0.4967 | 0.0961      | 0.1518 |
| 0.4083        | 8.82  | 3000  | 0.3119          | 0.4806 | 0.0926      | 0.1475 |
| 0.4234        | 9.41  | 3200  | 0.3117          | 0.4678 | 0.0896      | 0.1423 |
| 0.4318        | 10.0  | 3400  | 0.2938          | 0.4637 | 0.0881      | 0.1398 |
| 0.6403        | 10.59 | 3600  | 0.2960          | 0.4402 | 0.0855      | 0.1363 |
| 0.4015        | 11.18 | 3800  | 0.2955          | 0.4605 | 0.0868      | 0.1381 |
| 0.3722        | 11.76 | 4000  | 0.2806          | 0.4390 | 0.0832      | 0.1329 |
| 0.3153        | 12.35 | 4200  | 0.2801          | 0.4201 | 0.0817      | 0.1302 |
| 0.3262        | 12.94 | 4400  | 0.2681          | 0.4316 | 0.0816      | 0.1311 |
| 0.3238        | 13.53 | 4600  | 0.2685          | 0.4136 | 0.0786      | 0.1262 |
| 0.311         | 14.12 | 4800  | 0.2671          | 0.4018 | 0.0769      | 0.1231 |
| 0.3581        | 14.71 | 5000  | 0.2651          | 0.3968 | 0.0765      | 0.1228 |
| 0.3355        | 15.29 | 5200  | 0.2634          | 0.3970 | 0.0762      | 0.1225 |
| 0.5307        | 15.88 | 5400  | 0.2632          | 0.4007 | 0.0760      | 0.1226 |
| 0.3148        | 16.47 | 5600  | 0.2579          | 0.3964 | 0.0745      | 0.1202 |
| 0.3247        | 17.06 | 5800  | 0.2562          | 0.3825 | 0.0726      | 0.1176 |
| 0.3346        | 17.65 | 6000  | 0.2498          | 0.3895 | 0.0733      | 0.1183 |
| 0.2601        | 18.24 | 6200  | 0.2512          | 0.3924 | 0.0725      | 0.1176 |
| 0.2705        | 18.82 | 6400  | 0.2459          | 0.4010 | 0.0737      | 0.1198 |
| 0.2295        | 19.41 | 6600  | 0.2492          | 0.3826 | 0.0716      | 0.1159 |
| 0.3824        | 20.0  | 6800  | 0.2532          | 0.3820 | 0.0720      | 0.1163 |
| 0.3082        | 20.59 | 7000  | 0.2485          | 0.3796 | 0.0714      | 0.1157 |
| 0.2927        | 21.18 | 7200  | 0.2477          | 0.3807 | 0.0712      | 0.1155 |
| 0.3819        | 21.76 | 7400  | 0.2446          | 0.3729 | 0.0700      | 0.1139 |
| 0.2941        | 22.35 | 7600  | 0.2452          | 0.3740 | 0.0699      | 0.1138 |
| 0.3104        | 22.94 | 7800  | 0.2406          | 0.3699 | 0.0688      | 0.1126 |
| 0.2359        | 23.53 | 8000  | 0.2389          | 0.3731 | 0.0692      | 0.1129 |
| 0.2895        | 24.12 | 8200  | 0.2405          | 0.3613 | 0.0682      | 0.1114 |
| 0.2144        | 24.71 | 8400  | 0.2404          | 0.3686 | 0.0682      | 0.1115 |
| 0.3572        | 25.29 | 8600  | 0.2376          | 0.3769 | 0.0693      | 0.1133 |
| 0.3137        | 25.88 | 8800  | 0.2383          | 0.3660 | 0.0685      | 0.1115 |
| 0.2457        | 26.47 | 9000  | 0.2379          | 0.3688 | 0.0684      | 0.1115 |
| 0.2577        | 27.06 | 9200  | 0.2369          | 0.3707 | 0.0682      | 0.1119 |
| 0.3276        | 27.65 | 9400  | 0.2379          | 0.3621 | 0.0676      | 0.1105 |
| 0.2566        | 28.24 | 9600  | 0.2376          | 0.3637 | 0.0672      | 0.1104 |
| 0.2814        | 28.82 | 9800  | 0.2369          | 0.3652 | 0.0676      | 0.1107 |
| 0.2574        | 29.41 | 10000 | 0.2372          | 0.3614 | 0.0673      | 0.1102 |
| 0.5213        | 30.0  | 10200 | 0.2375          | 0.3633 | 0.0675      | 0.1103 |


### Framework versions

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