README.md

---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-conformer-rope-large-960h-ft
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: wav2vec2-conformer-rope-large-960h-ft-armenian-CV17.0
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: hy-AM
      split: None
      args: hy-AM
    metrics:
    - type: wer
      value: 0.990876791521137
      name: Wer
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-conformer-rope-large-960h-ft-armenian-CV17.0

This model is a fine-tuned version of [facebook/wav2vec2-conformer-rope-large-960h-ft](https://huggingface.co/facebook/wav2vec2-conformer-rope-large-960h-ft) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1627
- Wer: 0.9909
- Cer: 0.8400

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 4.2764        | 1.0   | 325  | 3.1252          | 1.0    | 0.9984 |
| 2.9396        | 2.0   | 650  | 3.1627          | 0.9909 | 0.8400 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1