---
library_name: transformers
license: apache-2.0
base_model: SIRIS-Lab/affilgood-affilroberta
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
---

<!-- 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. -->

# affilgood-span-v2 

This model is a fine-tuned version of [SIRIS-Lab/affilgood-affilroberta](https://huggingface.co/SIRIS-Lab/affilgood-affilroberta) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2360
- Precision: 0.8321
- Recall: 0.8934
- F1: 0.8617
- Accuracy: 0.9612

## 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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 93   | 0.1532          | 0.7861    | 0.8333 | 0.8090 | 0.9567   |
| No log        | 2.0   | 186  | 0.1135          | 0.8404    | 0.8634 | 0.8518 | 0.9610   |
| No log        | 3.0   | 279  | 0.1021          | 0.8333    | 0.9016 | 0.8661 | 0.9682   |
| No log        | 4.0   | 372  | 0.1183          | 0.8182    | 0.8852 | 0.8504 | 0.9673   |
| No log        | 5.0   | 465  | 0.1377          | 0.8564    | 0.8962 | 0.8758 | 0.9685   |
| 0.0987        | 6.0   | 558  | 0.1296          | 0.8575    | 0.9044 | 0.8803 | 0.9682   |
| 0.0987        | 7.0   | 651  | 0.1568          | 0.8583    | 0.8934 | 0.8755 | 0.9685   |
| 0.0987        | 8.0   | 744  | 0.2092          | 0.8575    | 0.8880 | 0.8725 | 0.9649   |
| 0.0987        | 9.0   | 837  | 0.2360          | 0.8321    | 0.8934 | 0.8617 | 0.9612   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1