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RichardErkhov/
dannoncaffeine_-_GPT2-124M-wikitext-v0.1-gguf

Name: dannoncaffeine_-_GPT2-124M-wikitext-v0.1-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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GPT2-124M-wikitext-v0.1 - GGUF

Model creator: https://huggingface.co/dannoncaffeine/
Original model: https://huggingface.co/dannoncaffeine/GPT2-124M-wikitext-v0.1/

Name	Quant method	Size
GPT2-124M-wikitext-v0.1.Q2_K.gguf	Q2_K	0.08GB
GPT2-124M-wikitext-v0.1.Q3_K_S.gguf	Q3_K_S	0.08GB
GPT2-124M-wikitext-v0.1.Q3_K.gguf	Q3_K	0.09GB
GPT2-124M-wikitext-v0.1.Q3_K_M.gguf	Q3_K_M	0.09GB
GPT2-124M-wikitext-v0.1.Q3_K_L.gguf	Q3_K_L	0.1GB
GPT2-124M-wikitext-v0.1.IQ4_XS.gguf	IQ4_XS	0.1GB
GPT2-124M-wikitext-v0.1.Q4_0.gguf	Q4_0	0.1GB
GPT2-124M-wikitext-v0.1.IQ4_NL.gguf	IQ4_NL	0.1GB
GPT2-124M-wikitext-v0.1.Q4_K_S.gguf	Q4_K_S	0.1GB
GPT2-124M-wikitext-v0.1.Q4_K.gguf	Q4_K	0.11GB
GPT2-124M-wikitext-v0.1.Q4_K_M.gguf	Q4_K_M	0.11GB
GPT2-124M-wikitext-v0.1.Q4_1.gguf	Q4_1	0.11GB
GPT2-124M-wikitext-v0.1.Q5_0.gguf	Q5_0	0.11GB
GPT2-124M-wikitext-v0.1.Q5_K_S.gguf	Q5_K_S	0.11GB
GPT2-124M-wikitext-v0.1.Q5_K.gguf	Q5_K	0.12GB
GPT2-124M-wikitext-v0.1.Q5_K_M.gguf	Q5_K_M	0.12GB
GPT2-124M-wikitext-v0.1.Q5_1.gguf	Q5_1	0.12GB
GPT2-124M-wikitext-v0.1.Q6_K.gguf	Q6_K	0.13GB
GPT2-124M-wikitext-v0.1.Q8_0.gguf	Q8_0	0.17GB

Original model description:

license: mit base_model: gpt2 tags:

generated_from_trainer model-index:
name: GPT2-124M-wikitext-v0.1 results: [] datasets:
wikitext pipeline_tag: text-generation co2_eq_emissions: emissions: 500 training_type: "fine-tuning" source: "mlco2" geographical_location: "Bucharest, Romania" hardware_used: "1 x RTX 4090 GPU"

🧠 GPT2-124M-wikitext-v0.1

This model is a fine-tuned version of gpt2 on the wikitext. It achieves the following results on the evaluation set:

Loss: 2.9841

Model description

This is a practical hands-on experience for better understanding 🤗 Transformers and 🤗 Datasets. This model is GPT2(124M) fine-tuned on wikitext(103-raw-v1) on 1 x RTX 4090.

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
3.1335	1.0	57467	3.0363
3.0643	2.0	114934	2.9968
3.0384	3.0	172401	2.9841

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

RichardErkhov/dannoncaffeine_-_GPT2-124M-wikitext-v0.1-gguf