README.md

---
library_name: transformers
language: en
license: mit
datasets:
- CogComp/trec
base_model:
- openai-community/gpt2
---

# Model Card: GPT-2-TREC

An in-domain GPT-2, pre-trained from scratch on the TREC dataset text.

## Model Details

### Description

This model is based on the [GPT-2](https://huggingface.co/openai-community/gpt2)
architecture and was pre-trained from scratch (in-domain) using the text in TREC dataset, excluding its test split.

- **Developed by:** [Cesar Gonzalez-Gutierrez](https://ceguel.es)
- **Funded by:** [ERC](https://erc.europa.eu)
- **Architecture:** GPT-2
- **Language:** English
- **License:** MIT
- **Base model:** [GPT-2](https://huggingface.co/openai-community/gpt2)

### Checkpoints

Intermediate checkpoints from the pre-training process are available and can be accessed using specific tags,
which correspond to training epochs and steps:

| Epoch | Step | Tags | |
|---|---|---|---|
| 1 | 51 | epoch-1 | step-51 |
| 5 | 255 | epoch-5 | step-255 |
| 10 | 511 | epoch-10 | step-511 |
| 20 | 1023 | epoch-20 | step-1023 |
| 40 | 2046 | epoch-40 | step-2046 |
| 60 | 3070 | epoch-60 | step-3070 |
| 80 | 4093 | epoch-80 | step-4093 |
| 100 | 5116 | epoch-100 | step-5116 |
| 120 | 6140 | epoch-120 | step-6140 |
| 140 | 7163 | epoch-140 | step-7163 |
| 160 | 8186 | epoch-160 | step-8186 |
| 180 | 9210 | epoch-180 | step-9210 |
| 199 | 10200 | epoch-199 | step-10200 |

To load a model from a specific intermediate checkpoint, use the `revision` parameter with the corresponding tag:
```python
from transformers import AutoModelForCausalLM

model = AutoModelForMaskedLM.from_pretrained("<model-name>", revision="<checkpoint-tag>")
```

### Sources

- **Paper:** [Information pending]

## Training Details

For more details on the training procedure, please refer to the base model's documentation:
[Training procedure](https://huggingface.co/openai-community/gpt2#training-procedure).

### Training Data

All texts from TREC dataset, excluding the test partition.

#### Training Hyperparameters

- **Precision:** fp16
- **Batch size:** 8
- **Gradient accumulation steps:** 12

## Uses

For typical use cases and limitations, please refer to the base model's guidance: 
[Inteded uses & limitations](https://huggingface.co/openai-community/gpt2#intended-uses--limitations).

## Bias, Risks, and Limitations

This model inherits potential risks and limitations from the base model. Refer to:
[Limitations and bias](https://huggingface.co/openai-community/gpt2#limitations-and-bias).

## Environmental Impact

- **Hardware Type:** NVIDIA A100 PCIE 40GB
- **Runtime:** 28.5
- **Cluster Provider:** [Artemisa](https://artemisa.ific.uv.es/web/)
- **Compute Region:** EU
- **Carbon Emitted:** 4.42 kg CO2 eq.
## Citation

**BibTeX:**

[More Information Needed]