---
base_model: KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align
library_name: transformers
metrics:
- accuracy
- precision
- recall
- f1
tags:
- generated_from_trainer
model-index:
- name: dfm1
  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. -->

# dfm1

This model is a fine-tuned version of [KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align](https://huggingface.co/KennethEnevoldsen/dfm-sentence-encoder-large-exp2-no-lang-align) on an unknown dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.8868
- Precision: 0.8861
- Recall: 0.8868
- F1: 0.8855
- Loss: 0.5432

## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Accuracy | Precision | Recall | F1     | Validation Loss |
|:-------------:|:-------:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
| No log        | 0.9412  | 8    | 0.7844   | 0.7464    | 0.7844 | 0.7612 | 0.7436          |
| No log        | 2.0     | 17   | 0.8999   | 0.8922    | 0.8999 | 0.8914 | 0.3252          |
| No log        | 2.9412  | 25   | 0.9214   | 0.9226    | 0.9214 | 0.9121 | 0.3213          |
| No log        | 4.0     | 34   | 0.9164   | 0.9235    | 0.9164 | 0.9176 | 0.3572          |
| No log        | 4.9412  | 42   | 0.8880   | 0.8875    | 0.8880 | 0.8857 | 0.3576          |
| No log        | 6.0     | 51   | 0.8907   | 0.8894    | 0.8907 | 0.8898 | 0.3993          |
| No log        | 6.9412  | 59   | 0.8822   | 0.8822    | 0.8822 | 0.8806 | 0.4444          |
| No log        | 8.0     | 68   | 0.8876   | 0.8867    | 0.8876 | 0.8865 | 0.4480          |
| No log        | 8.9412  | 76   | 0.8987   | 0.8978    | 0.8987 | 0.8979 | 0.4688          |
| No log        | 10.0    | 85   | 0.8984   | 0.8972    | 0.8984 | 0.8975 | 0.4845          |
| No log        | 10.9412 | 93   | 0.8895   | 0.8887    | 0.8895 | 0.8884 | 0.5172          |
| No log        | 12.0    | 102  | 0.8891   | 0.8882    | 0.8891 | 0.8881 | 0.5349          |
| No log        | 12.9412 | 110  | 0.8907   | 0.8897    | 0.8907 | 0.8896 | 0.5343          |
| No log        | 14.0    | 119  | 0.8895   | 0.8886    | 0.8895 | 0.8884 | 0.5374          |
| No log        | 14.9412 | 127  | 0.8868   | 0.8861    | 0.8868 | 0.8855 | 0.5317          |
| No log        | 16.0    | 136  | 0.8853   | 0.8847    | 0.8853 | 0.8839 | 0.5383          |
| No log        | 16.9412 | 144  | 0.8853   | 0.8847    | 0.8853 | 0.8839 | 0.5402          |
| No log        | 18.0    | 153  | 0.8865   | 0.8858    | 0.8865 | 0.8851 | 0.5429          |
| No log        | 18.8235 | 160  | 0.8868   | 0.8861    | 0.8868 | 0.8855 | 0.5432          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Tokenizers 0.19.1