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--- |
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language: he |
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datasets: |
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- MatanBenChorin/HebrewMetaphors |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: hebert-finetuned-hebrew-metaphor |
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results: [] |
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widget: |
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- text: "לטחון [SEP] להכנת קפה במקינטה יש לטחון את הקפה טחינה גסה יותר מאשר קפה לאספרסו" |
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- text: "לטחון [SEP] תעירו אותי כשיקרה עוד משהו מעניין, בינתיים אין מה לטחון את זה" |
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- text: "לבשל [SEP] השחקן השתמש ביכולותיו הפיזיות, הגובה והקפיצה שלו, כדי לבשל ולהבקיע שערים" |
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- text: "לבשל [SEP] שישי בבוקר זה זמן טוב כדי לבשל ארוחה יפה" |
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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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# hebert-finetuned-hebrew-metaphor |
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לחלום, |
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לחתוך, |
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לעוף, |
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לפרק, |
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להדליק, |
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לכבס, |
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לכופף, |
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לרסק, |
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לבשל, |
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למחוק, |
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לקפוץ, |
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לקרוע, |
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לקצור, |
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לרקוד, |
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לשבור, |
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לשדוד, |
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לשתות, |
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לטחון, |
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לתפור, |
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לזרוע |
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This model is a fine-tuned version of [avichr/heBERT](https://huggingface.co/avichr/heBERT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4682 |
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- Accuracy: 0.9510 |
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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: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 389 | 0.1813 | 0.9379 | |
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| 0.2546 | 2.0 | 778 | 0.2309 | 0.9479 | |
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| 0.08 | 3.0 | 1167 | 0.3342 | 0.9492 | |
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| 0.0298 | 4.0 | 1556 | 0.4076 | 0.9460 | |
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| 0.0298 | 5.0 | 1945 | 0.3803 | 0.9485 | |
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| 0.0105 | 6.0 | 2334 | 0.3674 | 0.9454 | |
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| 0.0077 | 7.0 | 2723 | 0.5356 | 0.9410 | |
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| 0.0088 | 8.0 | 3112 | 0.4776 | 0.9422 | |
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| 0.0044 | 9.0 | 3501 | 0.4258 | 0.9504 | |
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| 0.0044 | 10.0 | 3890 | 0.4305 | 0.9523 | |
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| 0.001 | 11.0 | 4279 | 0.4357 | 0.9548 | |
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| 0.0031 | 12.0 | 4668 | 0.4770 | 0.9473 | |
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| 0.0015 | 13.0 | 5057 | 0.4604 | 0.9523 | |
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| 0.0015 | 14.0 | 5446 | 0.4670 | 0.9510 | |
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| 0.0022 | 15.0 | 5835 | 0.4682 | 0.9510 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.13.1 |
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- Tokenizers 0.13.3 |
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