---
library_name: transformers
base_model: microsoft/infoxlm-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: vp-infoxlm-large-dsc
  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. -->

# vp-infoxlm-large-dsc

This model is a fine-tuned version of [microsoft/infoxlm-large](https://huggingface.co/microsoft/infoxlm-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6113
- Accuracy: 0.8706
- F1: 0.8705
- Precision: 0.8713
- Recall: 0.8706

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8771        | 1.0   | 3180  | 0.8099          | 0.6890   | 0.6914 | 0.7003    | 0.6890 |
| 0.5911        | 2.0   | 6360  | 0.5717          | 0.8014   | 0.8007 | 0.8107    | 0.8014 |
| 0.4608        | 3.0   | 9540  | 0.5323          | 0.8442   | 0.8442 | 0.8449    | 0.8442 |
| 0.407         | 4.0   | 12720 | 0.5047          | 0.8680   | 0.8679 | 0.8683    | 0.8680 |
| 0.3372        | 5.0   | 15900 | 0.6113          | 0.8706   | 0.8705 | 0.8713    | 0.8706 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1