metadata
language:
- ro
license: apache-2.0
base_model: iulik-pisik/vreme_model_base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- iulik-pisik/horoscop_vreme_base
metrics:
- wer
model-index:
- name: Horoscope Model Base - finetuned on weather
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Vreme ProTV
type: iulik-pisik/horoscop_vreme_base
config: default
split: test
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 11.89889025893958
Horoscope Model Base - finetuned on weather
This model is a fine-tuned version of iulik-pisik/vreme_model_base on the Vreme ProTV dataset. It achieves the following results on the evaluation set:
- Loss: 0.2407
- Wer: 11.8989
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 |
|---|---|---|---|---|
| 0.0227 | 6.02 | 1000 | 0.1744 | 13.2758 |
| 0.001 | 12.05 | 2000 | 0.2217 | 12.0222 |
| 0.0004 | 18.07 | 3000 | 0.2365 | 11.9194 |
| 0.0003 | 24.1 | 4000 | 0.2407 | 11.8989 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2