---
license: mit
base_model: microsoft/deberta-v3-small
tags:
- regression
model-index:
- name: deberta-v3-small-sp500-edgar-10k-markdown-1024-vN
  results: []
datasets:
- BEE-spoke-data/sp500-edgar-10k-markdown
language:
- en
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# deberta-v3-small-sp500-edgar-10k-markdown-1024-vN


this predicts the `ret` column of the training dataset, given the `text` column. Fine-tuned @ ctx 1024.


## Model description

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on BEE-spoke-data/sp500-edgar-10k-markdown

It achieves the following results on the evaluation set:
- Loss: 0.0005
- Mse: 0.0005




## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 30826
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0064        | 0.54  | 50   | 0.0006          | 0.0006 |
| 0.0043        | 1.08  | 100  | 0.0005          | 0.0005 |
| 0.0028        | 1.61  | 150  | 0.0006          | 0.0006 |
| 0.0025        | 2.15  | 200  | 0.0005          | 0.0005 |
| 0.0025        | 2.69  | 250  | 0.0005          | 0.0005 |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.2