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---
library_name: transformers
license: mit
base_model: KennethEnevoldsen/dfm-sentence-encoder-large
tags:
- generated_from_trainer
model-index:
- name: dfm_ED1
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_ED1
This model is a fine-tuned version of [KennethEnevoldsen/dfm-sentence-encoder-large](https://huggingface.co/KennethEnevoldsen/dfm-sentence-encoder-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5402
- F1-score: 0.9344
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 69 | 0.3134 | 0.9098 |
| No log | 2.0 | 138 | 0.4634 | 0.8843 |
| No log | 3.0 | 207 | 0.5135 | 0.9097 |
| No log | 4.0 | 276 | 0.4919 | 0.9179 |
| No log | 5.0 | 345 | 0.6858 | 0.8768 |
| No log | 6.0 | 414 | 0.8026 | 0.8843 |
| No log | 7.0 | 483 | 0.5402 | 0.9344 |
| 0.156 | 8.0 | 552 | 0.6149 | 0.9180 |
| 0.156 | 9.0 | 621 | 0.6310 | 0.9180 |
| 0.156 | 10.0 | 690 | 0.6423 | 0.9180 |
| 0.156 | 11.0 | 759 | 0.6514 | 0.9180 |
| 0.156 | 12.0 | 828 | 0.6594 | 0.9180 |
| 0.156 | 13.0 | 897 | 0.6656 | 0.9180 |
| 0.156 | 14.0 | 966 | 0.6712 | 0.9180 |
| 0.0 | 15.0 | 1035 | 0.6755 | 0.9180 |
| 0.0 | 16.0 | 1104 | 0.6792 | 0.9180 |
| 0.0 | 17.0 | 1173 | 0.6824 | 0.9180 |
| 0.0 | 18.0 | 1242 | 0.6844 | 0.9180 |
| 0.0 | 19.0 | 1311 | 0.6856 | 0.9180 |
| 0.0 | 20.0 | 1380 | 0.6861 | 0.9180 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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