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--- |
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base_model: xxxxxxxxx |
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tags: |
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- generated_from_trainer |
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datasets: |
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- AmazonScience/massive |
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metrics: |
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- f1 |
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model-index: |
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- name: massive_indo |
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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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# massive_indo |
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This model is a fine-tuned version of [xxxxxxxxx](https://huggingface.co/xxxxxxxxx) on the massive dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4772 |
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- F1: 0.9465 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 4.5227 | 0.7 | 100 | 4.4260 | 0.0998 | |
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| 3.9734 | 1.41 | 200 | 3.9864 | 0.2616 | |
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| 3.6121 | 2.11 | 300 | 3.5977 | 0.3561 | |
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| 3.2481 | 2.82 | 400 | 3.2366 | 0.4929 | |
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| 2.9212 | 3.52 | 500 | 2.9196 | 0.5677 | |
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| 2.5236 | 4.23 | 600 | 2.6016 | 0.6625 | |
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| 2.3089 | 4.93 | 700 | 2.3252 | 0.7196 | |
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| 2.0311 | 5.63 | 800 | 2.0840 | 0.7740 | |
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| 1.793 | 6.34 | 900 | 1.8612 | 0.8168 | |
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| 1.5913 | 7.04 | 1000 | 1.6588 | 0.8524 | |
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| 1.4071 | 7.75 | 1100 | 1.4833 | 0.8781 | |
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| 1.2169 | 8.45 | 1200 | 1.3214 | 0.8806 | |
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| 1.1085 | 9.15 | 1300 | 1.2012 | 0.8983 | |
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| 0.9752 | 9.86 | 1400 | 1.0659 | 0.9145 | |
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| 0.8891 | 10.56 | 1500 | 0.9672 | 0.9165 | |
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| 0.7205 | 11.27 | 1600 | 0.8726 | 0.9225 | |
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| 0.6869 | 11.97 | 1700 | 0.8065 | 0.9320 | |
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| 0.5818 | 12.68 | 1800 | 0.7458 | 0.9367 | |
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| 0.5437 | 13.38 | 1900 | 0.6843 | 0.9374 | |
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| 0.4759 | 14.08 | 2000 | 0.6411 | 0.9357 | |
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| 0.4674 | 14.79 | 2100 | 0.6010 | 0.9388 | |
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| 0.4305 | 15.49 | 2200 | 0.5682 | 0.9427 | |
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| 0.3862 | 16.2 | 2300 | 0.5369 | 0.9424 | |
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| 0.3564 | 16.9 | 2400 | 0.5208 | 0.9412 | |
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| 0.3292 | 17.61 | 2500 | 0.5022 | 0.9424 | |
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| 0.3237 | 18.31 | 2600 | 0.4903 | 0.9450 | |
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| 0.3187 | 19.01 | 2700 | 0.4807 | 0.9460 | |
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| 0.317 | 19.72 | 2800 | 0.4772 | 0.9465 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Tokenizers 0.13.3 |
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