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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-STEP8_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-STEP8_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: 0.0001
- Accuracy: 1.0
- F1: 1.0
- Precision: 1.0
- Recall: 1.0
- Accuracy Label Gd622:no: 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label Gd622:no | Accuracy Label Gd622:yes |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----------------------:|:------------------------:|
| 0.0992 | 0.1610 | 100 | 0.0070 | 0.9987 | 0.9987 | 0.9987 | 0.9987 | 0.9982 | 1.0 |
| 0.0082 | 0.3221 | 200 | 0.0002 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0002 | 0.4831 | 300 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 0.6441 | 400 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0001 | 0.8052 | 500 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |
| 0.0052 | 0.9662 | 600 | 0.0001 | 1.0 | 1.0 | 1.0 | 1.0 | 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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