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---
license: apache-2.0
base_model: albert/albert-base-v2
tags:
- trl
- sft
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: classify-ISIN-STEP7_binary
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# classify-ISIN-STEP7_binary
This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co./albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0
- Accuracy Label gd622:null: 0.0
- Accuracy Label Gd622:null: 1.0
- Accuracy Label Gd622:yes: 1.0
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label gd622:null | Accuracy Label Gd622:null | Accuracy Label Gd622:yes |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:---:|:---------:|:------:|:--------------------------:|:-------------------------:|:------------------------:|
| 0.2172 | 2.0833 | 100 | 0.1748 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0224 | 4.1667 | 200 | 0.0035 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0015 | 6.25 | 300 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0098 | 8.3333 | 400 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0094 | 10.4167 | 500 | 0.0004 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0003 | 12.5 | 600 | 0.0003 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0002 | 14.5833 | 700 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0002 | 16.6667 | 800 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
| 0.0002 | 18.75 | 900 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 0.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1
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