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--- |
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language: |
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- ro |
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base_model: iulik-udrik/vreme_model_tiny |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- iulik-pisik/vreme_horoscop_tiny |
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metrics: |
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- wer |
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model-index: |
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- name: Vreme Model Tiny - finetuned on horoscope |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Horoscop Neti Sandu |
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type: iulik-pisik/vreme_horoscop_tiny |
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config: default |
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split: None |
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args: 'config: ro, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 23.339011925042588 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Vreme Model Tiny - finetuned on horoscope |
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This model is a fine-tuned version of [iulik-udrik/vreme_model_tiny](https://huggingface.co/iulik-udrik/vreme_model_tiny) on the Horoscop Neti Sandu dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4493 |
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- Wer: 23.3390 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 4000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.0345 | 9.71 | 1000 | 0.3666 | 23.7527 | |
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| 0.0022 | 19.42 | 2000 | 0.4232 | 22.7306 | |
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| 0.0011 | 29.13 | 3000 | 0.4421 | 23.1930 | |
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| 0.0009 | 38.83 | 4000 | 0.4493 | 23.3390 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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