---
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: dfm
  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. -->

# Dialogue_dfm

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 the None dataset.
It achieves the following results on the evaluation set:
- Accuracy: 0.9417
- Precision: 0.9468
- Recall: 0.9417
- F1: 0.9418
- Loss: 0.4894

## 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    | 0.7223   | 0.7770    | 0.7223 | 0.7069 | 0.8079          |
| No log        | 2.0     | 17   | 0.7821   | 0.8280    | 0.7821 | 0.7670 | 0.7157          |
| No log        | 2.9412  | 25   | 0.9217   | 0.9243    | 0.9217 | 0.9174 | 0.3617          |
| No log        | 4.0     | 34   | 0.9283   | 0.9331    | 0.9283 | 0.9272 | 0.3444          |
| No log        | 4.9412  | 42   | 0.9156   | 0.9274    | 0.9156 | 0.9168 | 0.4618          |
| No log        | 6.0     | 51   | 0.9271   | 0.9316    | 0.9271 | 0.9277 | 0.3164          |
| No log        | 6.9412  | 59   | 0.9356   | 0.9387    | 0.9356 | 0.9349 | 0.3228          |
| No log        | 8.0     | 68   | 0.9329   | 0.9398    | 0.9329 | 0.9334 | 0.4814          |
| No log        | 8.9412  | 76   | 0.9402   | 0.9450    | 0.9402 | 0.9400 | 0.4819          |
| No log        | 10.0    | 85   | 0.9409   | 0.9459    | 0.9409 | 0.9409 | 0.4952          |
| No log        | 10.9412 | 93   | 0.9367   | 0.9428    | 0.9367 | 0.9370 | 0.5182          |
| No log        | 12.0    | 102  | 0.9409   | 0.9462    | 0.9409 | 0.9411 | 0.4947          |
| No log        | 12.9412 | 110  | 0.9405   | 0.9457    | 0.9405 | 0.9406 | 0.4927          |
| No log        | 14.0    | 119  | 0.9409   | 0.9462    | 0.9409 | 0.9411 | 0.4912          |
| No log        | 14.9412 | 127  | 0.9413   | 0.9465    | 0.9413 | 0.9414 | 0.4917          |
| No log        | 16.0    | 136  | 0.9413   | 0.9464    | 0.9413 | 0.9415 | 0.4893          |
| No log        | 16.9412 | 144  | 0.9413   | 0.9464    | 0.9413 | 0.9415 | 0.4890          |
| No log        | 18.0    | 153  | 0.9417   | 0.9468    | 0.9417 | 0.9418 | 0.4893          |
| No log        | 18.8235 | 160  | 0.9417   | 0.9468    | 0.9417 | 0.9418 | 0.4894          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1