gpt2-ohsumed / README.md
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---
library_name: transformers
language: en
license: mit
datasets:
- community-datasets/ohsumed
base_model:
- openai-community/gpt2
---
# Model Card: GPT-2-Ohsumed
An in-domain GPT-2, pre-trained from scratch on the Ohsumed 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 Ohsumed 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 | 97 | epoch-1 | step-97 |
| 5 | 489 | epoch-5 | step-489 |
| 10 | 978 | epoch-10 | step-978 |
| 20 | 1956 | epoch-20 | step-1956 |
| 40 | 3913 | epoch-40 | step-3913 |
| 60 | 5870 | epoch-60 | step-5870 |
| 80 | 7826 | epoch-80 | step-7826 |
| 100 | 9783 | epoch-100 | step-9783 |
| 120 | 11740 | epoch-120 | step-11740 |
| 140 | 13696 | epoch-140 | step-13696 |
| 160 | 15653 | epoch-160 | step-15653 |
| 180 | 17468 | epoch-180 | step-17468 |
| 200 | 19400 | epoch-200 | step-19400 |
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 Ohsumed 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:** 7 h
- **Cluster Provider:** [Artemisa](https://artemisa.ific.uv.es/web/)
- **Compute Region:** EU
- **Carbon Emitted:** 1.08 kg CO2 eq.
## Citation
**BibTeX:**
[More Information Needed]