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---
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: hs1024-nh32-nl24_custom
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: massive
type: massive
config: en-US
split: validation
args: en-US
metrics:
- name: Accuracy
type: accuracy
value: 0.05682582380632145
---
<!-- 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. -->
# hs1024-nh32-nl24_custom
This model is a fine-tuned version of [](https://huggingface.co/) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 3.7997
- Accuracy: 0.0568
## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.8643 | 0.35 | 500 | 3.8025 | 0.0516 |
| 3.8404 | 0.69 | 1000 | 3.8096 | 0.0443 |
| 3.888 | 1.04 | 1500 | 3.8620 | 0.0271 |
| 3.8807 | 1.39 | 2000 | 3.8388 | 0.0620 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.0
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