metadata
license: apache-2.0
base_model: teknium/OpenHermes-2.5-Mistral-7B
tags:
- generated_from_trainer
model-index:
- name: Eileithyia-7B
results: []
This model is a fine-tuned version of teknium/OpenHermes-2.5-Mistral-7B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4546
Model description
Eileithyia-7B is an unaligned, roleplay oriented model created by merging teknium/OpenHermes-2.5-Mistral-7B with a bespoke LORA trained directly on OpenHermes.
Eileithyia, as is the current trend, is named after a Greek goddess; in this case it is the goddess of childbirth and pregnancy.
Training and evaluation data
The private ~400k token dataset used to train the LORA was Alpaca formatted and focused on 4 primary categories:
- Medical texts (on pregnancy, reproductive organs, and impregnation). These are formatted so the model, in character as a doctor, answers a patient's question in short to medium form.
- Excerpts from short stories and novellas (erotic, romantic, and platonic) centered around both realistic and fantastic pregnancy. These are sliced into ~2048 token chunks, and these long-form responses are all tied to the command “Enter narrator mode.” in the instructions.
- A selection from PIPPA, using a wide keyword search for related terms then human curated (...the things I’ve seen…). These are converted to Alpaca with “Enter RP mode.” in all the instruction fields.
- ~60k tokens of GPT-4 generated data on pregnancy from various characters’ perspectives, focusing on different responses and stages. Also includes a synopsis for each week in various styles.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.5629 | 0.75 | 25 | 1.6511 |
| 1.5253 | 1.5 | 50 | 1.5730 |
| 1.3363 | 2.25 | 75 | 1.5014 |
| 1.4017 | 2.99 | 100 | 1.4690 |
| 1.2677 | 3.74 | 125 | 1.4593 |
| 1.351 | 4.49 | 150 | 1.4546 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1