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license: apache-2.0 |
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base_model: albert/albert-base-v2 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: classify-ISIN-STEP7_binary |
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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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# classify-ISIN-STEP7_binary |
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This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co./albert/albert-base-v2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0002 |
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- Accuracy: 1.0 |
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- F1: 1.0 |
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- Precision: 1.0 |
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- Recall: 1.0 |
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- Accuracy Label gd622:null: 0.0 |
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- Accuracy Label Gd622:null: 1.0 |
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- Accuracy Label Gd622:yes: 1.0 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label gd622:null | Accuracy Label Gd622:null | Accuracy Label Gd622:yes | |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|:--------------------------:|:-------------------------:|:------------------------:| |
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| 0.2172 | 2.0833 | 100 | 0.1748 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0224 | 4.1667 | 200 | 0.0035 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0015 | 6.25 | 300 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0098 | 8.3333 | 400 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0094 | 10.4167 | 500 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0003 | 12.5 | 600 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0002 | 14.5833 | 700 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0002 | 16.6667 | 800 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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| 0.0002 | 18.75 | 900 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.4.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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