WasamiKirua/Samantha-v0.1-ita-mistral-7B

See axolotl config

axolotl version: 0.4.0

base_model: DeepMount00/Mistral-Ita-7b
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer

load_in_8bit: false
load_in_4bit: false
strict: false

datasets:
  - path: /workspace/datasets/samantha-ita-sharegpt.jsonl
    type: sharegpt
    field: conversations
  - path: /workspace/datasets/psycology-dataset-gpt-ita.jsonl
    type: sharegpt
    field: conversations

chat_template: chatml

hub_model_id: Samantha-ita-v0.1
    
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./out

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false

wandb_project: samantha-mistral7b
wandb_entity:
wandb_watch:
wandb_name: Samantha-ita-v0.1
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000006

# 0.000006 OK better curve
# 0.0005 OK

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "<|im_end|>"
  unk_token: "<unk>"
tokens:
  - "<|im_start|>"
  - "<|im_end|>"

Samantha-ita-v0.1

This model is a fine-tuned version of DeepMount00/Mistral-Ita-7b on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.7069

Model description

Samantha is a fine-tuned Italian version based on Eric Hartford's Samantha. For this, I utilized the pre-trained Mistral 7B version. The model performs excellently! Please take a look at the datasets used.

Intended uses & limitations

Sure, here's the corrected and improved version:

Samantha is a proficient companion who understands and speaks Italian fluently. She has undergone training on various topics. In addition to the original Samantha dataset translated with GPT-4, I have also incorporated a psychology conversations dataset to further enrich Samantha's knowledge in the field of psychology."

Chat Template

<|im_start|>system
YOUR PROMPT<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Quantized Versions:

GGUF availabile here: https://huggingface.co./WasamiKirua/Samantha-ita-mistral-v0.1-GGUF

DPO Version

DPO trained version available here: https://huggingface.co./WasamiKirua/Samantha-ita-mistral-v0.1-DPO

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 6e-06
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 10
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
1.9261	0.01	1	1.8998
0.8902	0.25	28	0.8267
0.8422	0.5	56	0.7604
0.8338	0.75	84	0.7299
0.8397	1.0	112	0.7136
0.6859	1.22	140	0.7131
0.6707	1.47	168	0.7082
0.7041	1.72	196	0.7069
0.6936	1.97	224	0.7069

Framework versions

• Transformers 4.40.0.dev0
• Pytorch 2.2.0
• Datasets 2.15.0
• Tokenizers 0.15.0