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---
license: apache-2.0
base_model: Snowflake/snowflake-arctic-embed-m
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
model-index:
- name: stack-edu-scorer
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. -->
# stack-edu-scorer
This model is a fine-tuned version of [Snowflake/snowflake-arctic-embed-m](https://huggingface.co/Snowflake/snowflake-arctic-embed-m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3426
- Precision: 0.5188
- Recall: 0.3971
- F1 Macro: 0.4258
- Accuracy: 0.6350
## 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: 0.0003
- train_batch_size: 256
- eval_batch_size: 128
- seed: 0
- 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 | Precision | Recall | F1 Macro | Accuracy |
|:-------------:|:-------:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
| 0.3973 | 0.5787 | 1000 | 0.3904 | 0.4701 | 0.3433 | 0.3701 | 0.5885 |
| 0.3848 | 1.1574 | 2000 | 0.3803 | 0.5107 | 0.3574 | 0.3863 | 0.5974 |
| 0.3667 | 1.7361 | 3000 | 0.3715 | 0.6471 | 0.4478 | 0.4879 | 0.6103 |
| 0.3727 | 2.3148 | 4000 | 0.3655 | 0.6140 | 0.4375 | 0.4715 | 0.6121 |
| 0.3639 | 2.8935 | 5000 | 0.3617 | 0.6234 | 0.4519 | 0.4879 | 0.6176 |
| 0.3684 | 3.4722 | 6000 | 0.3626 | 0.6424 | 0.4632 | 0.5020 | 0.6211 |
| 0.3557 | 4.0509 | 7000 | 0.3589 | 0.5519 | 0.3739 | 0.4032 | 0.6175 |
| 0.3513 | 4.6296 | 8000 | 0.3650 | 0.6328 | 0.4671 | 0.5010 | 0.6241 |
| 0.3505 | 5.2083 | 9000 | 0.3535 | 0.5320 | 0.3850 | 0.4129 | 0.6259 |
| 0.3549 | 5.7870 | 10000 | 0.3526 | 0.6358 | 0.4588 | 0.4949 | 0.6248 |
| 0.3465 | 6.3657 | 11000 | 0.3580 | 0.5204 | 0.3712 | 0.3970 | 0.6166 |
| 0.3468 | 6.9444 | 12000 | 0.3498 | 0.5266 | 0.3936 | 0.4235 | 0.6293 |
| 0.3463 | 7.5231 | 13000 | 0.3497 | 0.6837 | 0.4661 | 0.4999 | 0.6300 |
| 0.3404 | 8.1019 | 14000 | 0.3557 | 0.6169 | 0.4940 | 0.5285 | 0.6307 |
| 0.3381 | 8.6806 | 15000 | 0.3493 | 0.5124 | 0.3871 | 0.4135 | 0.6290 |
| 0.342 | 9.2593 | 16000 | 0.3482 | 0.5265 | 0.3959 | 0.4247 | 0.6337 |
| 0.3397 | 9.8380 | 17000 | 0.3477 | 0.5210 | 0.3919 | 0.4191 | 0.6325 |
| 0.3407 | 10.4167 | 18000 | 0.3465 | 0.5380 | 0.3895 | 0.4202 | 0.6297 |
| 0.3303 | 10.9954 | 19000 | 0.3471 | 0.5273 | 0.3952 | 0.4234 | 0.6355 |
| 0.3296 | 11.5741 | 20000 | 0.3447 | 0.5428 | 0.3891 | 0.4173 | 0.6313 |
| 0.3299 | 12.1528 | 21000 | 0.3451 | 0.5173 | 0.3964 | 0.4248 | 0.6347 |
| 0.3316 | 12.7315 | 22000 | 0.3448 | 0.6321 | 0.4809 | 0.5167 | 0.6350 |
| 0.3289 | 13.3102 | 23000 | 0.3446 | 0.5100 | 0.3969 | 0.4242 | 0.6358 |
| 0.3278 | 13.8889 | 24000 | 0.3445 | 0.5451 | 0.3918 | 0.4223 | 0.6327 |
| 0.3249 | 14.4676 | 25000 | 0.3440 | 0.5282 | 0.3915 | 0.4194 | 0.6343 |
| 0.328 | 15.0463 | 26000 | 0.3438 | 0.5670 | 0.3880 | 0.4183 | 0.6316 |
| 0.3263 | 15.625 | 27000 | 0.3448 | 0.6290 | 0.4828 | 0.5191 | 0.6363 |
| 0.3243 | 16.2037 | 28000 | 0.3437 | 0.5534 | 0.3950 | 0.4252 | 0.6356 |
| 0.3265 | 16.7824 | 29000 | 0.3435 | 0.5432 | 0.3926 | 0.4217 | 0.6328 |
| 0.3193 | 17.3611 | 30000 | 0.3432 | 0.5231 | 0.3962 | 0.4238 | 0.6348 |
| 0.3261 | 17.9398 | 31000 | 0.3433 | 0.5517 | 0.3933 | 0.4235 | 0.6326 |
| 0.317 | 18.5185 | 32000 | 0.3431 | 0.5527 | 0.3929 | 0.4220 | 0.6334 |
| 0.3222 | 19.0972 | 33000 | 0.3429 | 0.5132 | 0.3976 | 0.4259 | 0.6357 |
| 0.3223 | 19.6759 | 34000 | 0.3426 | 0.5188 | 0.3971 | 0.4258 | 0.6350 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.19.1
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