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---
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
|