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---
library_name: transformers
license: mit
base_model: KennethEnevoldsen/dfm-sentence-encoder-large
tags:
- generated_from_trainer
model-index:
- name: dfm_ED
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_ED
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: 0.6486
- F1-score: 0.9180
## 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 | 0.4303 | 0.8683 |
| No log | 2.0 | 138 | 0.5203 | 0.8442 |
| No log | 3.0 | 207 | 0.6280 | 0.8926 |
| No log | 4.0 | 276 | 0.6846 | 0.9003 |
| No log | 5.0 | 345 | 0.7642 | 0.9014 |
| No log | 6.0 | 414 | 0.8076 | 0.9014 |
| No log | 7.0 | 483 | 0.8324 | 0.9014 |
| 0.1316 | 8.0 | 552 | 0.8670 | 0.9010 |
| 0.1316 | 9.0 | 621 | 1.2453 | 0.8499 |
| 0.1316 | 10.0 | 690 | 0.6486 | 0.9180 |
| 0.1316 | 11.0 | 759 | 1.1641 | 0.8671 |
| 0.1316 | 12.0 | 828 | 0.8504 | 0.9097 |
| 0.1316 | 13.0 | 897 | 0.8590 | 0.9096 |
| 0.1316 | 14.0 | 966 | 0.8651 | 0.9096 |
| 0.0051 | 15.0 | 1035 | 0.8829 | 0.8934 |
| 0.0051 | 16.0 | 1104 | 0.9813 | 0.8848 |
| 0.0051 | 17.0 | 1173 | 0.9844 | 0.8848 |
| 0.0051 | 18.0 | 1242 | 0.9857 | 0.8848 |
| 0.0051 | 19.0 | 1311 | 0.9858 | 0.8848 |
| 0.0051 | 20.0 | 1380 | 0.9859 | 0.8848 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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