---
language:
- ro
base_model: iulik-udrik/vreme_model_small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- iulik-pisik/vreme_horoscop_small
metrics:
- wer
model-index:
- name: Vreme Model Small - finetuned on horoscope
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Horoscop Neti Sandu
      type: iulik-pisik/vreme_horoscop_small
      config: default
      split: None
      args: 'config: ro, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 10.172791433438793
---

<!-- 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. -->

# Vreme Model Small - finetuned on horoscope

This model is a fine-tuned version of [iulik-udrik/vreme_model_small](https://huggingface.co/iulik-udrik/vreme_model_small) on the Horoscop Neti Sandu dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2529
- Wer: 10.1728

## 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: 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0047        | 9.71  | 1000 | 0.2062          | 10.5865 |
| 0.0004        | 19.42 | 2000 | 0.2349          | 10.4405 |
| 0.0002        | 29.13 | 3000 | 0.2488          | 10.2701 |
| 0.0002        | 38.83 | 4000 | 0.2529          | 10.1728 |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2