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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: 0.4792 |
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- F1 Micro: 0.6970 |
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- F1 Macro: 0.6089 |
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- Accuracy: 0.2104 |
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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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| 0.7081 | 0.2067 | 20 | 0.6048 | 0.6244 | 0.5113 | 0.1528 | |
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| 0.5228 | 0.4134 | 40 | 0.5096 | 0.6713 | 0.5815 | 0.1883 | |
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| 0.5048 | 0.6202 | 60 | 0.4928 | 0.7002 | 0.5865 | 0.2155 | |
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| 0.5129 | 0.8269 | 80 | 0.4792 | 0.6970 | 0.6089 | 0.2104 | |
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| 0.4842 | 1.0336 | 100 | 0.4801 | 0.6972 | 0.6023 | 0.2369 | |
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| 0.3372 | 1.2403 | 120 | 0.5545 | 0.6687 | 0.5877 | 0.1761 | |
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| 0.3302 | 1.4470 | 140 | 0.5374 | 0.6895 | 0.6020 | 0.2019 | |
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| 0.3342 | 1.6537 | 160 | 0.5330 | 0.6860 | 0.5993 | 0.2117 | |
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| 0.3392 | 1.8605 | 180 | 0.5190 | 0.6894 | 0.5913 | 0.2006 | |
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| 0.2844 | 2.0672 | 200 | 0.5853 | 0.6891 | 0.5819 | 0.2369 | |
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| 0.1458 | 2.2739 | 220 | 0.7038 | 0.6743 | 0.5749 | 0.2097 | |
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| 0.1508 | 2.4806 | 240 | 0.6808 | 0.6802 | 0.5834 | 0.1994 | |
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| 0.1481 | 2.6873 | 260 | 0.7026 | 0.6773 | 0.5721 | 0.2 | |
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| 0.1378 | 2.8941 | 280 | 0.7336 | 0.6790 | 0.5768 | 0.2162 | |
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| 0.0961 | 3.1008 | 300 | 0.8397 | 0.6709 | 0.5465 | 0.2272 | |
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| 0.0552 | 3.3075 | 320 | 0.8260 | 0.6743 | 0.5654 | 0.2168 | |
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| 0.0509 | 3.5142 | 340 | 0.8692 | 0.6777 | 0.5666 | 0.2233 | |
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| 0.0489 | 3.7209 | 360 | 0.8505 | 0.6874 | 0.5722 | 0.2388 | |
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| 0.0526 | 3.9276 | 380 | 0.8269 | 0.6842 | 0.5778 | 0.2233 | |
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| 0.0278 | 4.1344 | 400 | 0.9280 | 0.6813 | 0.5557 | 0.2414 | |
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| 0.0187 | 4.3411 | 420 | 0.9390 | 0.6829 | 0.5588 | 0.2382 | |
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| 0.0169 | 4.5478 | 440 | 0.9510 | 0.6834 | 0.5612 | 0.2485 | |
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| 0.0158 | 4.7545 | 460 | 0.9325 | 0.6819 | 0.5612 | 0.2427 | |
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| 0.0161 | 4.9612 | 480 | 0.9311 | 0.6822 | 0.5634 | 0.2440 | |
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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 |
