| --- |
| language: |
| - ro |
| license: apache-2.0 |
| base_model: openai/whisper-tiny |
| tags: |
| - hf-asr-leaderboard |
| - generated_from_trainer |
| datasets: |
| - iulik-pisik/horoscop_neti |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Tiny Romanian - Horoscop Neti |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: Horoscop Neti |
| type: iulik-pisik/horoscop_neti |
| config: default |
| split: None |
| args: 'config: ro, split: test' |
| metrics: |
| - name: Wer |
| type: wer |
| value: 21.854465806765635 |
| --- |
| |
| <!-- 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 Tiny Romanian - Horoscop Neti |
|
|
| This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Horoscop Neti dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4305 |
| - Wer: 21.8545 |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:-------:| |
| | 0.0401 | 9.71 | 1000 | 0.3338 | 22.5116 | |
| | 0.0027 | 19.42 | 2000 | 0.3979 | 22.5359 | |
| | 0.0013 | 29.13 | 3000 | 0.4230 | 22.0248 | |
| | 0.001 | 38.83 | 4000 | 0.4305 | 21.8545 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.38.1 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.1 |
| - Tokenizers 0.15.2 |
| |
