metadata
language:
- ro
base_model: iulik-udrik/vreme_model_base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- iulik-pisik/vreme_horoscop_base
metrics:
- wer
model-index:
- name: Vreme Model base - finetuned on horoscope
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Horoscop Neti Sandu
type: iulik-pisik/vreme_horoscop_base
config: default
split: None
args: 'config: ro, split: test'
metrics:
- name: Wer
type: wer
value: 17.66853248965685
Vreme Model base - finetuned on horoscope
This model is a fine-tuned version of iulik-pisik/vreme_model_base on the Horoscop Neti Sandu dataset. It achieves the following results on the evaluation set:
- Loss: 0.3471
- Wer: 17.6685
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 |
|---|---|---|---|---|
| 0.0111 | 9.71 | 1000 | 0.2991 | 18.3986 |
| 0.001 | 19.42 | 2000 | 0.3298 | 17.9119 |
| 0.0006 | 29.13 | 3000 | 0.3422 | 17.4252 |
| 0.0005 | 38.83 | 4000 | 0.3471 | 17.6685 |
Framework versions
- Transformers 4.39.1
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2