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---
license: mit
base_model: intfloat/multilingual-e5-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: miner-24_e5
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. -->
# miner-24_e5
This model is a fine-tuned version of [intfloat/multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8934
- Accuracy: 0.796
- Ball: 0.125
- Precision: 0.0995
- Recall: 0.125
- F1: 0.1108
## 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: 0.0001
- 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Ball | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:---------:|:------:|:------:|
| 1.4223 | 1.0 | 624 | 0.8490 | 0.796 | 0.125 | 0.0995 | 0.125 | 0.1108 |
| 1.3854 | 2.0 | 1248 | 0.8556 | 0.796 | 0.125 | 0.0995 | 0.125 | 0.1108 |
| 1.3709 | 3.0 | 1872 | 0.8934 | 0.796 | 0.125 | 0.0995 | 0.125 | 0.1108 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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