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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+pygm-350m-experimental - AWQ
+- Model creator: https://huggingface.co/alpindale/
+- Original model: https://huggingface.co/alpindale/pygm-350m-experimental/
+
+
+
+
+Original model description:
+---
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: pygmalion-350m
+  results: []
+---
+
+# pygmalion-350m
+
+This model is a fine-tuned version of [PygmalionAI/pygmalion-350m](https://huggingface.co/PygmalionAI/pygmalion-350m/) on a 2.4MB dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2731
+- Accuracy: 0.5187
+
+## Model description
+
+A proof-of-concept model based on PygmalionAI/pygmalion-350m, which was in turn based on OPT-350m.
+
+This model was fine-tuned purely for testing purposes.
+
+## Fine-tuning process
+
+Fine-tuned on an A100-80GB with HF's `run_clm.py` script. It was run through 3 epochs with 8 batch size using 2.4MB dataset (split 75/25 between training and validation sets).
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-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: 3.0
+
+### Framework versions
+
+- Transformers 4.27.0.dev0
+- Pytorch 1.13.1+cu117
+- Datasets 2.10.0
+- Tokenizers 0.13.2
+
+