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

# dfm_indirect_speech

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: 0.9158
- Precision: 0.9150
- Recall: 0.9158
- F1: 0.9099
- Loss: 0.6465

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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        | 1.0   | 13   | 0.8602   | 0.8484    | 0.8602 | 0.8492 | 0.4979          |
| No log        | 2.0   | 26   | 0.8809   | 0.8636    | 0.8809 | 0.8718 | 0.4677          |
| No log        | 3.0   | 39   | 0.9062   | 0.8906    | 0.9062 | 0.8973 | 0.3820          |
| No log        | 4.0   | 52   | 0.9290   | 0.9110    | 0.9290 | 0.9194 | 0.4183          |
| No log        | 5.0   | 65   | 0.9018   | 0.8924    | 0.9018 | 0.8958 | 0.3585          |
| No log        | 6.0   | 78   | 0.8939   | 0.8984    | 0.8939 | 0.8855 | 0.5402          |
| No log        | 7.0   | 91   | 0.9171   | 0.9105    | 0.9171 | 0.9131 | 0.4350          |
| No log        | 8.0   | 104  | 0.9255   | 0.9198    | 0.9255 | 0.9196 | 0.4858          |
| No log        | 9.0   | 117  | 0.9242   | 0.9259    | 0.9242 | 0.9161 | 0.5378          |
| No log        | 10.0  | 130  | 0.9177   | 0.9153    | 0.9177 | 0.9114 | 0.5865          |
| No log        | 11.0  | 143  | 0.9181   | 0.9169    | 0.9181 | 0.9120 | 0.6122          |
| No log        | 12.0  | 156  | 0.9163   | 0.9154    | 0.9163 | 0.9102 | 0.6229          |
| No log        | 13.0  | 169  | 0.9165   | 0.9146    | 0.9165 | 0.9106 | 0.6222          |
| No log        | 14.0  | 182  | 0.9154   | 0.9127    | 0.9154 | 0.9096 | 0.6227          |
| No log        | 15.0  | 195  | 0.9146   | 0.9141    | 0.9146 | 0.9088 | 0.6326          |
| No log        | 16.0  | 208  | 0.9154   | 0.9146    | 0.9154 | 0.9095 | 0.6406          |
| No log        | 17.0  | 221  | 0.9154   | 0.9146    | 0.9154 | 0.9095 | 0.6462          |
| No log        | 18.0  | 234  | 0.9158   | 0.9150    | 0.9158 | 0.9099 | 0.6458          |
| No log        | 18.48 | 240  | 0.9158   | 0.9150    | 0.9158 | 0.9099 | 0.6465          |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Tokenizers 0.21.0