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--- |
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library_name: transformers |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Muaalem-model-dev |
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results: [] |
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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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# Muaalem-model-dev |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0212 |
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- Per Phonemes: 0.0058 |
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- Per Hams Or Jahr: 0.0026 |
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- Per Shidda Or Rakhawa: 0.0040 |
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- Per Tafkheem Or Taqeeq: 0.0030 |
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- Per Itbaq: 0.0019 |
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- Per Safeer: 0.0022 |
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- Per Qalqla: 0.0020 |
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- Per Tikraar: 0.0023 |
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- Per Tafashie: 0.0160 |
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- Per Istitala: 0.0019 |
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- Per Ghonna: 0.0027 |
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- Average Per: 0.0040 |
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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: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 90 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Per Phonemes | Per Hams Or Jahr | Per Shidda Or Rakhawa | Per Tafkheem Or Taqeeq | Per Itbaq | Per Safeer | Per Qalqla | Per Tikraar | Per Tafashie | Per Istitala | Per Ghonna | Average Per | |
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|:-------------:|:------:|:----:|:---------------:|:------------:|:----------------:|:---------------------:|:----------------------:|:---------:|:----------:|:----------:|:-----------:|:------------:|:------------:|:----------:|:-----------:| |
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| 0.8303 | 0.2022 | 73 | 0.1027 | 0.0612 | 0.0229 | 0.0245 | 0.1080 | 0.0327 | 0.0658 | 0.0270 | 0.0433 | 0.2467 | 0.0236 | 0.0243 | 0.0618 | |
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| 0.0593 | 0.4044 | 146 | 0.0451 | 0.0207 | 0.0041 | 0.0055 | 0.0066 | 0.0032 | 0.0042 | 0.0042 | 0.0032 | 0.0566 | 0.0029 | 0.0038 | 0.0105 | |
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| 0.0434 | 0.6066 | 219 | 0.0306 | 0.0081 | 0.0031 | 0.0043 | 0.0032 | 0.0021 | 0.0025 | 0.0026 | 0.0028 | 0.0322 | 0.0024 | 0.0034 | 0.0061 | |
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| 0.032 | 0.8089 | 292 | 0.0212 | 0.0058 | 0.0026 | 0.0040 | 0.0030 | 0.0019 | 0.0022 | 0.0020 | 0.0023 | 0.0160 | 0.0019 | 0.0027 | 0.0040 | |
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### Framework versions |
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- Transformers 4.55.0 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.4 |
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