Text Generation
Transformers
PyTorch
llama
Generated from Trainer
axolotl
conversational
Inference Endpoints
text-generation-inference
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Dolphin 2.9.3 Yi 1.5 34b 32k 🐬

Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations

Discord Discord: https://discord.gg/cognitivecomputations

Our appreciation for the sponsors of Dolphin 2.9.3:

This model is based on Yi-1.5-34b-32k, and is governed by the apache 2.0 license.

The base model has 32k context, and our finetuning took place with 8192 sequence length.

Dolphin 2.9.3 uses ChatML prompt template format.

example:

<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Dolphin-2.9.3 has a variety of instruction following, conversational, and coding skills. It also has initial agentic abilities and supports function calling.

Dolphin is uncensored. We have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.

Dolphin is licensed according to apache 2.0 license. We grant permission for any use, including commercial. Dolphin was trained on data generated from GPT4, among other models.

Evals

image/png

Training

Built with Axolotl

See axolotl config

axolotl version: 0.4.0

base_model: 01-ai/Yi-1.5-34B-32k
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true

# load_in_8bit: false
load_in_4bit: true
# strict: false

adapter: qlora
lora_modules_to_save: [embed_tokens, lm_head]

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: false
lora_fan_in_fan_out:

datasets:
  - path: /workspace/datasets/dolphin-2.9.3/dolphin201-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/SystemChat_filtered_sharegpt.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/SystemChat_multilingual_sharegpt.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-translate-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/dolphin-coder-codegen-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/not_samantha_norefusals.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/Orca-Math-resort-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/agent_instruct_react_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/toolbench_instruct_j1s1_3k_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/toolbench_negative_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/toolbench_react_10p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/toolbench_tflan_cot_30p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9.3/openhermes200k_unfiltered.jsonl
    type: sharegpt 
    conversation: chatml

chat_template: chatml

dataset_prepared_path: dolphin-2.9.3-yi34b-prepared
val_set_size: 0.01
output_dir: ./dolphin-2.9.3-out

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true

wandb_project: dolphin-2.9.3-yi-1.5-34b
wandb_watch:
wandb_run_id:
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 1
num_epochs: 3
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 1e-5

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

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
# evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 4
save_total_limit: 2
save_steps:
debug:
deepspeed: /workspace/axolotl/deepspeed_configs/zero3_bf16.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<|startoftext|>"
  eos_token: "<|im_end|>"
  pad_token: "<unk>"
  unk_token: "<unk>"
tokens:
  - "<|im_start|>"

#unfrozen_parameters:
lora_target_modules:
  # input_layernorm layers
  # - model.layers.0.input_layernorm
  # - model.layers.1.input_layernorm
  # - model.layers.2.input_layernorm
  # - model.layers.3.input_layernorm
  # - model.layers.4.input_layernorm
  # - model.layers.5.input_layernorm
  # - model.layers.6.input_layernorm
  # - model.layers.7.input_layernorm
  # - model.layers.8.input_layernorm
  # - model.layers.9.input_layernorm
  # - model.layers.10.input_layernorm
  # - model.layers.11.input_layernorm
  # - model.layers.12.input_layernorm
  # - model.layers.13.input_layernorm
  # - model.layers.14.input_layernorm
  # - model.layers.15.input_layernorm
  # - model.layers.16.input_layernorm
  # - model.layers.17.input_layernorm
  # - model.layers.18.input_layernorm
  # - model.layers.19.input_layernorm
  # - model.layers.20.input_layernorm
  # - model.layers.21.input_layernorm
  # - model.layers.22.input_layernorm
  # - model.layers.23.input_layernorm
  # - model.layers.24.input_layernorm
  # - model.layers.25.input_layernorm
  # - model.layers.26.input_layernorm
  # - model.layers.27.input_layernorm
  # - model.layers.28.input_layernorm
  # - model.layers.29.input_layernorm
  - lm_head
  # mlp.down_proj layers
  - model.layers.44.mlp.down_proj
  - model.layers.45.mlp.down_proj
  - model.layers.46.mlp.down_proj
  - model.layers.47.mlp.down_proj
  - model.layers.43.mlp.down_proj
  - model.layers.48.mlp.down_proj
  - model.layers.49.mlp.down_proj
  - model.layers.42.mlp.down_proj
  - model.layers.50.mlp.down_proj
  - model.layers.41.mlp.down_proj
  - model.layers.51.mlp.down_proj
  - model.layers.52.mlp.down_proj
  - model.layers.39.mlp.down_proj
  - model.layers.40.mlp.down_proj
  - model.layers.53.mlp.down_proj
  - model.layers.54.mlp.down_proj
  - model.layers.38.mlp.down_proj
  - model.layers.56.mlp.down_proj
  - model.layers.55.mlp.down_proj
  - model.layers.37.mlp.down_proj
  - model.layers.36.mlp.down_proj
  - model.layers.57.mlp.down_proj
  - model.layers.35.mlp.down_proj
  - model.layers.12.mlp.down_proj
  - model.layers.13.mlp.down_proj
  - model.layers.16.mlp.down_proj
  - model.layers.14.mlp.down_proj
  - model.layers.11.mlp.down_proj
  - model.layers.34.mlp.down_proj
  - model.layers.17.mlp.down_proj
  # mlp.gate_proj layers
  - model.layers.57.mlp.gate_proj
  - model.layers.58.mlp.gate_proj
  - model.layers.56.mlp.gate_proj
  - model.layers.55.mlp.gate_proj
  - model.layers.54.mlp.gate_proj
  - model.layers.35.mlp.gate_proj
  - model.layers.34.mlp.gate_proj
  - model.layers.53.mlp.gate_proj
  - model.layers.26.mlp.gate_proj
  - model.layers.52.mlp.gate_proj
  - model.layers.25.mlp.gate_proj
  - model.layers.33.mlp.gate_proj
  - model.layers.51.mlp.gate_proj
  - model.layers.18.mlp.gate_proj
  - model.layers.32.mlp.gate_proj
  - model.layers.36.mlp.gate_proj
  - model.layers.24.mlp.gate_proj
  - model.layers.17.mlp.gate_proj
  - model.layers.23.mlp.gate_proj
  - model.layers.31.mlp.gate_proj
  - model.layers.50.mlp.gate_proj
  - model.layers.19.mlp.gate_proj
  - model.layers.15.mlp.gate_proj
  - model.layers.27.mlp.gate_proj
  - model.layers.37.mlp.gate_proj
  - model.layers.14.mlp.gate_proj
  - model.layers.39.mlp.gate_proj
  - model.layers.11.mlp.gate_proj
  - model.layers.29.mlp.gate_proj
  - model.layers.28.mlp.gate_proj
  # mlp.up_proj layers
  - model.layers.21.mlp.up_proj
  - model.layers.48.mlp.up_proj
  - model.layers.49.mlp.up_proj
  - model.layers.24.mlp.up_proj
  - model.layers.47.mlp.up_proj
  - model.layers.25.mlp.up_proj
  - model.layers.23.mlp.up_proj
  - model.layers.50.mlp.up_proj
  - model.layers.14.mlp.up_proj
  - model.layers.46.mlp.up_proj
  - model.layers.26.mlp.up_proj
  - model.layers.27.mlp.up_proj
  - model.layers.20.mlp.up_proj
  - model.layers.13.mlp.up_proj
  - model.layers.51.mlp.up_proj
  - model.layers.28.mlp.up_proj
  - model.layers.45.mlp.up_proj
  - model.layers.22.mlp.up_proj
  - model.layers.52.mlp.up_proj
  - model.layers.12.mlp.up_proj
  - model.layers.29.mlp.up_proj
  - model.layers.44.mlp.up_proj
  - model.layers.53.mlp.up_proj
  - model.layers.11.mlp.up_proj
  - model.layers.42.mlp.up_proj
  - model.layers.30.mlp.up_proj
  - model.layers.43.mlp.up_proj
  - model.layers.19.mlp.up_proj
  - model.layers.54.mlp.up_proj
  - model.layers.40.mlp.up_proj
  - model.embed_tokens
  # model.norm layers
  # post_attention_layernorm layers
  # - model.layers.0.post_attention_layernorm
  # - model.layers.1.post_attention_layernorm
  # - model.layers.2.post_attention_layernorm
  # - model.layers.3.post_attention_layernorm
  # - model.layers.4.post_attention_layernorm
  # - model.layers.5.post_attention_layernorm
  # - model.layers.6.post_attention_layernorm
  # - model.layers.7.post_attention_layernorm
  # - model.layers.8.post_attention_layernorm
  # - model.layers.9.post_attention_layernorm
  # - model.layers.10.post_attention_layernorm
  # - model.layers.11.post_attention_layernorm
  # - model.layers.12.post_attention_layernorm
  # - model.layers.13.post_attention_layernorm
  # - model.layers.14.post_attention_layernorm
  # - model.layers.15.post_attention_layernorm
  # - model.layers.16.post_attention_layernorm
  # - model.layers.17.post_attention_layernorm
  # - model.layers.18.post_attention_layernorm
  # - model.layers.19.post_attention_layernorm
  # - model.layers.20.post_attention_layernorm
  # - model.layers.21.post_attention_layernorm
  # - model.layers.22.post_attention_layernorm
  # - model.layers.23.post_attention_layernorm
  # - model.layers.24.post_attention_layernorm
  # - model.layers.25.post_attention_layernorm
  # - model.layers.26.post_attention_layernorm
  # - model.layers.27.post_attention_layernorm
  # - model.layers.28.post_attention_layernorm
  # - model.layers.29.post_attention_layernorm
  # self_attn.k_proj layers
  - model.layers.55.self_attn.k_proj
  - model.layers.51.self_attn.k_proj
  - model.layers.53.self_attn.k_proj
  - model.layers.56.self_attn.k_proj
  - model.layers.54.self_attn.k_proj
  - model.layers.57.self_attn.k_proj
  - model.layers.52.self_attn.k_proj
  - model.layers.59.self_attn.k_proj
  - model.layers.49.self_attn.k_proj
  - model.layers.48.self_attn.k_proj
  - model.layers.47.self_attn.k_proj
  - model.layers.41.self_attn.k_proj
  - model.layers.58.self_attn.k_proj
  - model.layers.40.self_attn.k_proj
  - model.layers.46.self_attn.k_proj
  - model.layers.44.self_attn.k_proj
  - model.layers.50.self_attn.k_proj
  - model.layers.43.self_attn.k_proj
  - model.layers.39.self_attn.k_proj
  - model.layers.42.self_attn.k_proj
  - model.layers.45.self_attn.k_proj
  - model.layers.33.self_attn.k_proj
  - model.layers.37.self_attn.k_proj
  - model.layers.17.self_attn.k_proj
  - model.layers.24.self_attn.k_proj
  - model.layers.21.self_attn.k_proj
  - model.layers.25.self_attn.k_proj
  - model.layers.23.self_attn.k_proj
  - model.layers.35.self_attn.k_proj
  - model.layers.20.self_attn.k_proj
  # self_attn.o_proj layers
  - model.layers.53.self_attn.o_proj
  - model.layers.55.self_attn.o_proj
  - model.layers.54.self_attn.o_proj
  - model.layers.42.self_attn.o_proj
  - model.layers.52.self_attn.o_proj
  - model.layers.51.self_attn.o_proj
  - model.layers.50.self_attn.o_proj
  - model.layers.1.self_attn.o_proj
  - model.layers.40.self_attn.o_proj
  - model.layers.37.self_attn.o_proj
  - model.layers.34.self_attn.o_proj
  - model.layers.36.self_attn.o_proj
  - model.layers.41.self_attn.o_proj
  - model.layers.35.self_attn.o_proj
  - model.layers.46.self_attn.o_proj
  - model.layers.27.self_attn.o_proj
  - model.layers.33.self_attn.o_proj
  - model.layers.30.self_attn.o_proj
  - model.layers.43.self_attn.o_proj
  - model.layers.39.self_attn.o_proj
  - model.layers.17.self_attn.o_proj
  - model.layers.28.self_attn.o_proj
  - model.layers.48.self_attn.o_proj
  - model.layers.31.self_attn.o_proj
  - model.layers.29.self_attn.o_proj
  - model.layers.38.self_attn.o_proj
  - model.layers.47.self_attn.o_proj
  - model.layers.56.self_attn.o_proj
  - model.layers.32.self_attn.o_proj
  - model.layers.4.self_attn.o_proj
  # self_attn.q_proj layers
  - model.layers.1.self_attn.q_proj
  - model.layers.3.self_attn.q_proj
  - model.layers.4.self_attn.q_proj
  - model.layers.5.self_attn.q_proj
  - model.layers.2.self_attn.q_proj
  - model.layers.0.self_attn.q_proj
  - model.layers.6.self_attn.q_proj
  - model.layers.8.self_attn.q_proj
  - model.layers.7.self_attn.q_proj
  - model.layers.10.self_attn.q_proj
  - model.layers.36.self_attn.q_proj
  - model.layers.11.self_attn.q_proj
  - model.layers.9.self_attn.q_proj
  - model.layers.35.self_attn.q_proj
  - model.layers.28.self_attn.q_proj
  - model.layers.34.self_attn.q_proj
  - model.layers.27.self_attn.q_proj
  - model.layers.14.self_attn.q_proj
  - model.layers.29.self_attn.q_proj
  - model.layers.12.self_attn.q_proj
  - model.layers.33.self_attn.q_proj
  - model.layers.30.self_attn.q_proj
  - model.layers.24.self_attn.q_proj
  - model.layers.32.self_attn.q_proj
  - model.layers.37.self_attn.q_proj
  - model.layers.20.self_attn.q_proj
  - model.layers.15.self_attn.q_proj
  - model.layers.16.self_attn.q_proj
  - model.layers.26.self_attn.q_proj
  - model.layers.31.self_attn.q_proj
  # self_attn.v_proj layers
  - model.layers.7.self_attn.v_proj
  - model.layers.8.self_attn.v_proj
  - model.layers.9.self_attn.v_proj
  - model.layers.10.self_attn.v_proj
  - model.layers.12.self_attn.v_proj
  - model.layers.13.self_attn.v_proj
  - model.layers.14.self_attn.v_proj
  - model.layers.15.self_attn.v_proj
  - model.layers.16.self_attn.v_proj
  - model.layers.17.self_attn.v_proj
  - model.layers.21.self_attn.v_proj
  - model.layers.23.self_attn.v_proj
  - model.layers.39.self_attn.v_proj
  - model.layers.46.self_attn.v_proj
  - model.layers.48.self_attn.v_proj
  - model.layers.49.self_attn.v_proj
  - model.layers.51.self_attn.v_proj
  - model.layers.52.self_attn.v_proj
  - model.layers.53.self_attn.v_proj
  - model.layers.54.self_attn.v_proj
  - model.layers.55.self_attn.v_proj
  - model.layers.56.self_attn.v_proj
  - model.layers.22.self_attn.v_proj
  - model.layers.18.self_attn.v_proj
  - model.layers.50.self_attn.v_proj
  - model.layers.47.self_attn.v_proj
  - model.layers.44.self_attn.v_proj
  - model.layers.45.self_attn.v_proj
  - model.layers.57.self_attn.v_proj
  - model.layers.41.self_attn.v_proj
  

out-yi

This model is a fine-tuned version of 01-ai/Yi-1.5-34B on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4425

Model description

More information needed

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: 1e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • total_eval_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: 3

Training results

Training Loss Epoch Step Validation Loss
0.6265 0.0 1 0.6035
0.4674 0.25 327 0.4344
0.4337 0.5 654 0.4250
0.4346 0.75 981 0.4179
0.3985 1.0 1308 0.4118
0.3128 1.23 1635 0.4201
0.3261 1.48 1962 0.4157
0.3259 1.73 2289 0.4122
0.3126 1.98 2616 0.4079
0.2265 2.21 2943 0.4441
0.2297 2.46 3270 0.4427
0.2424 2.71 3597 0.4425

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.2+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Datasets used to train cognitivecomputations/dolphin-2.9.3-Yi-1.5-34B-32k