---
language:
- en
tags:
- generated_from_trainer
metrics:
- accuracy
license: apache-2.0
datasets:
- BEE-spoke-data/fineweb-100k_en-med
---


# MiniLMv2-L6-H384_R-fineweb-100k

This is a MiniLMv2 model continually pre-trained on an MLM task with the goal of improving downstream fine-tuning/performance:

- activation updated to SiLU prior to further training
- MLM @ 40% mask ratio

## Model description

This model is a fine-tuned version of [nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large](https://huggingface.co/nreimers/MiniLMv2-L6-H384-distilled-from-RoBERTa-Large) on the BEE-spoke-data/fineweb-100k_en-med dataset.

It achieves the following results on the evaluation set:
- Loss: 4.0206
- Accuracy: 0.3783
- Num Input Tokens Seen: 162790400

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 8e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1792
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-07
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 100
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| 4.6583        | 0.1208 | 150  | 4.5052          | 0.3406   | 9830400           |
| 4.5365        | 0.2415 | 300  | 4.3712          | 0.3525   | 19660800          |
| 4.4621        | 0.3623 | 450  | 4.2810          | 0.3575   | 29491200          |
| 4.4116        | 0.4831 | 600  | 4.2466          | 0.3615   | 39321600          |
| 4.3487        | 0.6038 | 750  | 4.1795          | 0.3661   | 49152000          |
| 4.338         | 0.7246 | 900  | 4.1874          | 0.3663   | 58982400          |
| 4.342         | 0.8454 | 1050 | 4.1475          | 0.3695   | 68812800          |
| 4.268         | 0.9661 | 1200 | 4.1215          | 0.3714   | 78643200          |
| 4.2185        | 1.0869 | 1350 | 4.1032          | 0.3725   | 88472576          |
| 4.2645        | 1.2077 | 1500 | 4.0859          | 0.3757   | 98302976          |
| 4.2542        | 1.3284 | 1650 | 4.0730          | 0.3750   | 108133376         |
| 4.2614        | 1.4492 | 1800 | 4.0682          | 0.3749   | 117963776         |
| 4.1928        | 1.5700 | 1950 | 4.0596          | 0.3758   | 127794176         |
| 4.1971        | 1.6907 | 2100 | 4.0505          | 0.3777   | 137624576         |
| 4.1966        | 1.8115 | 2250 | 4.0163          | 0.3787   | 147454976         |
| 4.16          | 1.9323 | 2400 | 4.0352          | 0.3774   | 157285376         |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1