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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
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
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: 0.9981
- Precision: 0.9980
- Recall: 0.9981
- F1: 0.9979
- Loss: 0.0066
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1 | Validation Loss |
|:-------------:|:------:|:----:|:--------:|:---------:|:------:|:------:|:---------------:|
| No log | 0.9524 | 10 | 0.9116 | 0.8719 | 0.9116 | 0.8909 | 0.3402 |
| No log | 2.0 | 21 | 0.9585 | 0.9581 | 0.9585 | 0.9535 | 0.1368 |
| No log | 2.9524 | 31 | 0.9818 | 0.9806 | 0.9818 | 0.9812 | 0.0664 |
| No log | 4.0 | 42 | 0.9926 | 0.9912 | 0.9926 | 0.9919 | 0.0286 |
| No log | 4.9524 | 52 | 0.9947 | 0.9934 | 0.9947 | 0.9940 | 0.0209 |
| No log | 6.0 | 63 | 0.9953 | 0.9941 | 0.9953 | 0.9946 | 0.0159 |
| No log | 6.9524 | 73 | 0.9967 | 0.9968 | 0.9967 | 0.9963 | 0.0107 |
| No log | 8.0 | 84 | 0.9977 | 0.9977 | 0.9977 | 0.9975 | 0.0082 |
| No log | 8.9524 | 94 | 0.9980 | 0.9979 | 0.9980 | 0.9978 | 0.0067 |
| No log | 9.5238 | 100 | 0.9981 | 0.9980 | 0.9981 | 0.9979 | 0.0066 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1
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