README.md

---
language:
- en
license: apache-2.0
base_model: EleutherAI/pythia-31m
datasets:
- totally-not-an-llm/EverythingLM-data-V3
- databricks/databricks-dolly-15k
- THUDM/webglm-qa
- starfishmedical/webGPT_x_dolly
- Amod/mental_health_counseling_conversations
- sablo/oasst2_curated
- cognitivecomputations/wizard_vicuna_70k_unfiltered
- mlabonne/chatml_dpo_pairs
pipeline_tag: text-generation
widget:
 - messages:
 - role: system
 content: >-
 You are a career counselor. The user will provide you with an individual
 looking for guidance in their professional life, and your task is to assist
 them in determining what careers they are most suited for based on their skills,
 interests, and experience. You should also conduct research into the various
 options available, explain the job market trends in different industries, and
 advice on which qualifications would be beneficial for pursuing particular fields.
 - role: user
 content: Heya!
 - role: assistant
 content: Hi! How may I help you?
 - role: user
 content: >-
 I am interested in developing a career in software engineering. What
 would you recommend me to do?
 - messages:
 - role: system
 content: "You are a helpful assistant who answers user's questions with details and curiosity."
 - role: user
 content: What are some potential applications for quantum computing?
 - messages:
 - role: system
 content: You are a highly knowledgeable assistant. Help the user as much as you can.
 - role: user
 content: What are some steps I can take to become a healthier person?
inference:
 parameters:
 max_new_tokens: 250
 penalty_alpha: 0.5
 top_k: 2
 repetition_penalty: 1.0016
model-index:
- name: Pythia-31M-Chat-v1
 results:
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: AI2 Reasoning Challenge (25-Shot)
 type: ai2_arc
 config: ARC-Challenge
 split: test
 args:
 num_few_shot: 25
 metrics:
 - type: acc_norm
 value: 22.7
 name: normalized accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Pythia-31M-Chat-v1
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: HellaSwag (10-Shot)
 type: hellaswag
 split: validation
 args:
 num_few_shot: 10
 metrics:
 - type: acc_norm
 value: 25.6
 name: normalized accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Pythia-31M-Chat-v1
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: MMLU (5-Shot)
 type: cais/mmlu
 config: all
 split: test
 args:
 num_few_shot: 5
 metrics:
 - type: acc
 value: 23.24
 name: accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Pythia-31M-Chat-v1
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: Winogrande (5-shot)
 type: winogrande
 config: winogrande_xl
 split: validation
 args:
 num_few_shot: 5
 metrics:
 - type: acc
 value: 47.99
 name: accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Pythia-31M-Chat-v1
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: TruthfulQA (0-shot)
 type: truthful_qa
 config: multiple_choice
 split: validation
 args:
 num_few_shot: 0
 metrics:
 - type: mc2
 value: 0.0
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Pythia-31M-Chat-v1
 name: Open LLM Leaderboard
 - task:
 type: text-generation
 name: Text Generation
 dataset:
 name: GSM8k (5-shot)
 type: gsm8k
 config: main
 split: test
 args:
 num_few_shot: 5
 metrics:
 - type: acc
 value: 0.0
 name: accuracy
 source:
 url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Felladrin/Pythia-31M-Chat-v1
 name: Open LLM Leaderboard
---

# A Pythia Chat Model of 31M Parameters

- Base model: [EleutherAI/pythia-31m](https://huggingface.co/EleutherAI/pythia-31m)
- Availability in other ML formats:
 - GGUF: [Felladrin/gguf-Pythia-31M-Chat-v1](https://huggingface.co/Felladrin/gguf-Pythia-31M-Chat-v1)
 - ONNX: [Felladrin/onnx-Pythia-31M-Chat-v1](https://huggingface.co/Felladrin/onnx-Pythia-31M-Chat-v1)

## Recommended prompt format

```
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
```

## Recommended inference parameters

```yml
penalty_alpha: 0.5
top_k: 2
repetition_penalty: 1.0016
```

## Datasets and parameters used for training

| Dataset | License Type |
|---------|--------------|
| [totally-not-an-llm/EverythingLM-data-V3](https://huggingface.co/datasets/totally-not-an-llm/EverythingLM-data-V3) | mit |
| [databricks/databricks-dolly-15k](https://huggingface.co/datasets/databricks/databricks-dolly-15k) | cc-by-sa-3.0 |
| [THUDM/webglm-qa](https://huggingface.co/datasets/THUDM/webglm-qa) | apache-2.0 |
| [starfishmedical/webGPT_x_dolly](https://huggingface.co/datasets/starfishmedical/webGPT_x_dolly) | cc-by-sa-3.0 |
| [Amod/mental_health_counseling_conversations](https://huggingface.co/datasets/Amod/mental_health_counseling_conversations) | openrail |
| [sablo/oasst2_curated](https://huggingface.co/datasets/sablo/oasst2_curated) | apache-2.0 |
| [cognitivecomputations/wizard_vicuna_70k_unfiltered](https://huggingface.co/datasets/cognitivecomputations/wizard_vicuna_70k_unfiltered) | apache-2.0 |
| [mlabonne/chatml_dpo_pairs](https://huggingface.co/datasets/mlabonne/chatml_dpo_pairs) | apache-2.0 |

```python
SFTTrainer(
 model,
 train_dataset=train_dataset,
 dataset_text_field="text",
 eval_dataset=eval_dataset,
 max_seq_length=2048,
 packing=True,
 args=TrainingArguments(
 learning_rate=2e-6,
 per_device_train_batch_size=1,
 per_device_eval_batch_size=1,
 gradient_accumulation_steps=16,
 lr_scheduler_type="cosine",
 num_train_epochs=1,
 logging_strategy="steps",
 save_strategy="steps",
 evaluation_strategy="steps",
 logging_steps=10,
 eval_steps=10,
 save_steps=10,
 warmup_steps=50,
 load_best_model_at_end=True,
 metric_for_best_model="eval_loss",
 greater_is_better=False,
 weight_decay=0.01,
 save_total_limit=10,
 neftune_noise_alpha=5,
 ),
 callbacks=[
 EarlyStoppingCallback(
 early_stopping_patience=3,
 early_stopping_threshold=0.005
 ),
 ],
)
```

```python
DPOTrainer(
 model,
 beta=0.1,
 train_dataset=dataset,
 tokenizer=tokenizer,
 eval_dataset=eval_dataset,
 max_length=1536,
 max_prompt_length=1024,
 args=TrainingArguments(
 learning_rate=2e-6,
 per_device_train_batch_size=1,
 per_device_eval_batch_size=1,
 gradient_accumulation_steps=1,
 lr_scheduler_type="cosine",
 num_train_epochs=1,
 logging_strategy="steps",
 save_strategy="steps",
 evaluation_strategy="steps",
 logging_steps=1,
 eval_steps=1,
 save_steps=1,
 warmup_steps=0,
 load_best_model_at_end=True,
 metric_for_best_model="eval_loss",
 greater_is_better=False,
 weight_decay=0.0,
 neftune_noise_alpha=5,
 remove_unused_columns=False,
 ),
 callbacks=[
 EarlyStoppingCallback(
 early_stopping_patience=3,
 early_stopping_threshold=0.005
 ),
 ],
)
```

## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Felladrin__Pythia-31M-Chat-v1)

| Metric |Value|
|---------------------------------|----:|
|Avg. |19.92|
|AI2 Reasoning Challenge (25-Shot)|22.70|
|HellaSwag (10-Shot) |25.60|
|MMLU (5-Shot) |23.24|
|TruthfulQA (0-shot) | 0.00|
|Winogrande (5-shot) |47.99|
|GSM8k (5-shot) | 0.00|