---
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