transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer sq dataset:CV_Albanian base_model:openai/whisper-medium license:apache-2.0 endpoints_compatible region:us
---
language:
- sq
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- CV_Albanian
model-index:
- name: Whisper Medium CV Test
  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. -->

# Whisper Medium CV Test

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the CV Albanian dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.7844
- eval_wer: 39.9593
- eval_runtime: 186.4098
- eval_samples_per_second: 2.06
- eval_steps_per_second: 0.257
- epoch: 37.04
- step: 2000

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0338        | 0.2   | 500  | 0.7342          | 45.9470 |
| 0.0026        | 0.4   | 1000 | 0.7724          | 40.4887 |
| 0.0008        | 0.8   | 1500 | 0.7513          | 39.7148 |
| 0.0001        | 1.0   | 2000 | 0.7844          | 39.9592 |

### Training hyperparameters


The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- 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: 500
- training_steps: 5000

### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
