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--- |
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license: gemma |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: google/gemma-1.1-2b-it |
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metrics: |
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- accuracy |
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model-index: |
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- name: emotions_google_gemma |
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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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# emotions_google_gemma |
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This model is a fine-tuned version of [google/gemma-1.1-2b-it](https://huggingface.co./google/gemma-1.1-2b-it) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4858 |
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- F1 Micro: 0.6961 |
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- F1 Macro: 0.6067 |
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- Accuracy: 0.2369 |
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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: 0.0001 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:--------:| |
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| 0.7307 | 0.2067 | 20 | 0.6081 | 0.6151 | 0.4711 | 0.1709 | |
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| 0.5276 | 0.4134 | 40 | 0.5106 | 0.6760 | 0.5729 | 0.1676 | |
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| 0.5081 | 0.6202 | 60 | 0.4978 | 0.6922 | 0.5857 | 0.2006 | |
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| 0.5091 | 0.8269 | 80 | 0.4853 | 0.6908 | 0.6038 | 0.2052 | |
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| 0.4823 | 1.0336 | 100 | 0.4858 | 0.6961 | 0.6067 | 0.2369 | |
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| 0.3346 | 1.2403 | 120 | 0.5500 | 0.6663 | 0.5728 | 0.1702 | |
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| 0.3245 | 1.4470 | 140 | 0.5440 | 0.6816 | 0.5819 | 0.2052 | |
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| 0.3375 | 1.6537 | 160 | 0.5541 | 0.6808 | 0.5853 | 0.1987 | |
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| 0.3407 | 1.8605 | 180 | 0.5275 | 0.6875 | 0.5872 | 0.1916 | |
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| 0.2745 | 2.0672 | 200 | 0.6019 | 0.6928 | 0.5784 | 0.2311 | |
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| 0.1312 | 2.2739 | 220 | 0.7540 | 0.6750 | 0.5614 | 0.2097 | |
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| 0.1363 | 2.4806 | 240 | 0.7292 | 0.6805 | 0.5712 | 0.2078 | |
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| 0.1302 | 2.6873 | 260 | 0.7316 | 0.6846 | 0.5795 | 0.2045 | |
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| 0.125 | 2.8941 | 280 | 0.7491 | 0.6819 | 0.5711 | 0.2104 | |
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| 0.0877 | 3.1008 | 300 | 0.8069 | 0.6805 | 0.5651 | 0.2330 | |
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| 0.0457 | 3.3075 | 320 | 0.8849 | 0.6867 | 0.5592 | 0.2356 | |
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| 0.0453 | 3.5142 | 340 | 0.8583 | 0.6774 | 0.5626 | 0.2246 | |
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| 0.0429 | 3.7209 | 360 | 0.8338 | 0.6812 | 0.5675 | 0.2227 | |
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| 0.0463 | 3.9276 | 380 | 0.8497 | 0.6823 | 0.5735 | 0.2272 | |
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| 0.0256 | 4.1344 | 400 | 0.9236 | 0.6759 | 0.5607 | 0.2278 | |
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| 0.0155 | 4.3411 | 420 | 0.9380 | 0.6871 | 0.5651 | 0.2421 | |
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| 0.0127 | 4.5478 | 440 | 0.9505 | 0.6852 | 0.5646 | 0.2414 | |
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| 0.0129 | 4.7545 | 460 | 0.9438 | 0.6837 | 0.5658 | 0.2382 | |
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| 0.0123 | 4.9612 | 480 | 0.9431 | 0.6843 | 0.5666 | 0.2401 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
