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---
library_name: transformers
license: mit
base_model: mateiaassAI/teacher_sst2
tags:
- generated_from_trainer
datasets:
- laroseda
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: teacher_sst2_laroseda
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: laroseda
type: laroseda
config: laroseda
split: train
args: laroseda
metrics:
- name: F1
type: f1
value: 0.9489953582155384
- name: Accuracy
type: accuracy
value: 0.949
- name: Precision
type: precision
value: 0.9490837535014006
- name: Recall
type: recall
value: 0.949
---
<!-- 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. -->
# teacher_sst2_laroseda
This model is a fine-tuned version of [mateiaassAI/teacher_sst2](https://huggingface.co/mateiaassAI/teacher_sst2) on the laroseda dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1906
- F1: 0.9490
- Roc Auc: 0.9490
- Accuracy: 0.949
- Precision: 0.9491
- Recall: 0.949
## 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: 1.7e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|:---------:|:------:|
| 0.1799 | 1.0 | 688 | 0.1426 | 0.9435 | 0.9434 | 0.943 | 0.9441 | 0.943 |
| 0.1071 | 2.0 | 1376 | 0.1906 | 0.9490 | 0.9490 | 0.949 | 0.9491 | 0.949 |
### Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
|