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---
license: mit
base_model: intfloat/multilingual-e5-small
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: multi-e5-small_lmd-comments_v1
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. -->
# multi-e5-small_lmd-comments_v1
This model is a fine-tuned version of [intfloat/multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9808
- F1: 0.7036
- Accuracy: 0.7122
## 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: 2e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 1.0969 | 0.04 | 100 | 1.0991 | 0.4109 | 0.4964 |
| 1.0764 | 0.08 | 200 | 1.0768 | 0.5217 | 0.5971 |
| 0.955 | 0.12 | 300 | 0.9313 | 0.5802 | 0.6691 |
| 0.8137 | 0.17 | 400 | 0.8927 | 0.5864 | 0.6475 |
| 0.7837 | 0.21 | 500 | 0.8711 | 0.6238 | 0.6475 |
| 0.7234 | 0.25 | 600 | 0.9953 | 0.5641 | 0.6475 |
| 0.6983 | 0.29 | 700 | 0.9111 | 0.6226 | 0.6475 |
| 0.6574 | 0.33 | 800 | 0.8557 | 0.6686 | 0.6835 |
| 0.6653 | 0.37 | 900 | 0.7925 | 0.7087 | 0.7122 |
| 0.6444 | 0.41 | 1000 | 0.8338 | 0.7056 | 0.7122 |
| 0.6155 | 0.46 | 1100 | 0.8339 | 0.7257 | 0.7338 |
| 0.5726 | 0.5 | 1200 | 0.8078 | 0.7140 | 0.7194 |
| 0.6279 | 0.54 | 1300 | 0.9534 | 0.6917 | 0.7050 |
| 0.6083 | 0.58 | 1400 | 0.9515 | 0.6914 | 0.7050 |
| 0.5525 | 0.62 | 1500 | 0.9281 | 0.6846 | 0.7050 |
| 0.6849 | 0.66 | 1600 | 0.8352 | 0.6917 | 0.7050 |
| 0.5924 | 0.7 | 1700 | 1.0702 | 0.6602 | 0.6906 |
| 0.5614 | 0.75 | 1800 | 0.9689 | 0.6801 | 0.6978 |
| 0.5936 | 0.79 | 1900 | 1.0179 | 0.6896 | 0.7050 |
| 0.5582 | 0.83 | 2000 | 0.8858 | 0.7320 | 0.7410 |
| 0.5479 | 0.87 | 2100 | 0.9373 | 0.7030 | 0.7122 |
| 0.6278 | 0.91 | 2200 | 0.8694 | 0.6858 | 0.6978 |
| 0.4819 | 0.95 | 2300 | 0.9440 | 0.7074 | 0.7194 |
| 0.5425 | 0.99 | 2400 | 1.0661 | 0.6765 | 0.6906 |
| 0.5804 | 1.04 | 2500 | 0.8904 | 0.7189 | 0.7266 |
| 0.5025 | 1.08 | 2600 | 1.0105 | 0.6886 | 0.7050 |
| 0.5148 | 1.12 | 2700 | 0.9934 | 0.7076 | 0.7194 |
| 0.5359 | 1.16 | 2800 | 0.9249 | 0.7291 | 0.7410 |
| 0.5002 | 1.2 | 2900 | 0.7503 | 0.7047 | 0.7050 |
| 0.4563 | 1.24 | 3000 | 0.8149 | 0.7230 | 0.7266 |
| 0.4837 | 1.28 | 3100 | 0.8956 | 0.7125 | 0.7194 |
| 0.4486 | 1.33 | 3200 | 0.9013 | 0.7110 | 0.7194 |
| 0.4721 | 1.37 | 3300 | 1.0545 | 0.7142 | 0.7266 |
| 0.5482 | 1.41 | 3400 | 1.0139 | 0.7014 | 0.7122 |
| 0.4488 | 1.45 | 3500 | 0.9427 | 0.7162 | 0.7266 |
| 0.4859 | 1.49 | 3600 | 1.1337 | 0.7074 | 0.7194 |
| 0.504 | 1.53 | 3700 | 1.0299 | 0.7178 | 0.7266 |
| 0.4555 | 1.57 | 3800 | 0.8830 | 0.7273 | 0.7338 |
| 0.502 | 1.62 | 3900 | 1.0340 | 0.7142 | 0.7266 |
| 0.5131 | 1.66 | 4000 | 1.0997 | 0.7031 | 0.7194 |
| 0.5208 | 1.7 | 4100 | 1.0845 | 0.7025 | 0.7194 |
| 0.4329 | 1.74 | 4200 | 1.0553 | 0.7132 | 0.7266 |
| 0.4612 | 1.78 | 4300 | 1.0458 | 0.7074 | 0.7194 |
| 0.4857 | 1.82 | 4400 | 0.9425 | 0.7120 | 0.7194 |
| 0.4986 | 1.86 | 4500 | 0.9965 | 0.7237 | 0.7338 |
| 0.4066 | 1.91 | 4600 | 0.9520 | 0.7041 | 0.7122 |
| 0.4638 | 1.95 | 4700 | 0.9558 | 0.6979 | 0.7050 |
| 0.4541 | 1.99 | 4800 | 0.9808 | 0.7036 | 0.7122 |
### Framework versions
- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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