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dolphin-2.9-mixtral-8x22b

Text Generation
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mixtral
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axolotl
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dolphin-2.9-mixtral-8x22b / README.md
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metadata
license: apache-2.0
base_model: mistral-community/Mixtral-8x22B-v0.1
tags:
  - generated_from_trainer
model-index:
  - name: out
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.0

base_model: mistral-community/Mixtral-8x22B-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: LlamaTokenizer
trust_remote_code: true

load_in_8bit: false
load_in_4bit: false
strict: false

unfrozen_parameters:
  - ^lm_head.weight$
  - ^model.embed_tokens.weight$
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  - model.layers.1.block_sparse_moe.experts.6.w2
  - model.layers.0.block_sparse_moe.experts.6.w2
  - model.layers.6.block_sparse_moe.experts.6.w2
  - model.layers.7.block_sparse_moe.experts.6.w2
  - model.layers.8.block_sparse_moe.experts.6.w2
  - model.layers.9.block_sparse_moe.experts.6.w2
  - model.layers.10.block_sparse_moe.experts.6.w2
  - model.layers.11.block_sparse_moe.experts.6.w2
  - model.layers.12.block_sparse_moe.experts.6.w2
  - model.layers.13.block_sparse_moe.experts.6.w2
  - model.layers.5.block_sparse_moe.experts.6.w3
  - model.layers.4.block_sparse_moe.experts.6.w3
  - model.layers.3.block_sparse_moe.experts.6.w3
  - model.layers.2.block_sparse_moe.experts.6.w3
  - model.layers.1.block_sparse_moe.experts.6.w3
  - model.layers.0.block_sparse_moe.experts.6.w3
  - model.layers.6.block_sparse_moe.experts.6.w3
  - model.layers.7.block_sparse_moe.experts.6.w3
  - model.layers.8.block_sparse_moe.experts.6.w3
  - model.layers.9.block_sparse_moe.experts.6.w3
  - model.layers.10.block_sparse_moe.experts.6.w3
  - model.layers.11.block_sparse_moe.experts.6.w3
  - model.layers.12.block_sparse_moe.experts.6.w3
  - model.layers.13.block_sparse_moe.experts.6.w3
  - model.layers.5.block_sparse_moe.experts.7.w1
  - model.layers.6.block_sparse_moe.experts.7.w1
  - model.layers.3.block_sparse_moe.experts.7.w1
  - model.layers.4.block_sparse_moe.experts.7.w1
  - model.layers.2.block_sparse_moe.experts.7.w1
  - model.layers.0.block_sparse_moe.experts.7.w1
  - model.layers.7.block_sparse_moe.experts.7.w1
  - model.layers.8.block_sparse_moe.experts.7.w1
  - model.layers.9.block_sparse_moe.experts.7.w1
  - model.layers.10.block_sparse_moe.experts.7.w1
  - model.layers.11.block_sparse_moe.experts.7.w1
  - model.layers.12.block_sparse_moe.experts.7.w1
  - model.layers.13.block_sparse_moe.experts.7.w1
  - model.layers.14.block_sparse_moe.experts.7.w1
  - model.layers.6.block_sparse_moe.experts.7.w2
  - model.layers.5.block_sparse_moe.experts.7.w2
  - model.layers.4.block_sparse_moe.experts.7.w2
  - model.layers.2.block_sparse_moe.experts.7.w2
  - model.layers.3.block_sparse_moe.experts.7.w2
  - model.layers.1.block_sparse_moe.experts.7.w2
  - model.layers.0.block_sparse_moe.experts.7.w2
  - model.layers.7.block_sparse_moe.experts.7.w2
  - model.layers.8.block_sparse_moe.experts.7.w2
  - model.layers.9.block_sparse_moe.experts.7.w2
  - model.layers.10.block_sparse_moe.experts.7.w2
  - model.layers.11.block_sparse_moe.experts.7.w2
  - model.layers.12.block_sparse_moe.experts.7.w2
  - model.layers.13.block_sparse_moe.experts.7.w2
  - model.layers.6.block_sparse_moe.experts.7.w3
  - model.layers.5.block_sparse_moe.experts.7.w3
  - model.layers.4.block_sparse_moe.experts.7.w3
  - model.layers.3.block_sparse_moe.experts.7.w3
  - model.layers.2.block_sparse_moe.experts.7.w3
  - model.layers.0.block_sparse_moe.experts.7.w3
  - model.layers.7.block_sparse_moe.experts.7.w3
  - model.layers.8.block_sparse_moe.experts.7.w3
  - model.layers.9.block_sparse_moe.experts.7.w3
  - model.layers.10.block_sparse_moe.experts.7.w3
  - model.layers.11.block_sparse_moe.experts.7.w3
  - model.layers.12.block_sparse_moe.experts.7.w3
  - model.layers.13.block_sparse_moe.experts.7.w3
  - model.layers.14.block_sparse_moe.experts.7.w3
  # - model.layers.0.block_sparse_moe.gate
  # - model.layers.1.block_sparse_moe.gate
  # - model.layers.2.block_sparse_moe.gate
  # - model.layers.3.block_sparse_moe.gate
  # - model.layers.4.block_sparse_moe.gate
  # - model.layers.5.block_sparse_moe.gate
  # - model.layers.6.block_sparse_moe.gate
  # - model.layers.7.block_sparse_moe.gate
  # - model.layers.8.block_sparse_moe.gate
  # - model.layers.9.block_sparse_moe.gate
  # - model.layers.10.block_sparse_moe.gate
  # - model.layers.11.block_sparse_moe.gate
  # - model.layers.12.block_sparse_moe.gate
  # - model.layers.13.block_sparse_moe.gate
  
model_config:
  output_router_logits: true

datasets:
  - path: /workspace/datasets/dolphin-2.9/dolphin201-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/Ultrachat200kunfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-translate-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-codegen-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/not_samantha_norefusals.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/Orca-Math-resort-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/agent_instruct_react_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_instruct_j1s1_3k_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_negative_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_react_10p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_tflan_cot_30p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/openhermes200k_unfiltered.jsonl
    type: sharegpt 
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/SystemConversations.jsonl
    type: sharegpt
    conversation: chatml

chat_template: chatml

dataset_prepared_path: thingy
val_set_size: 0.0002
output_dir: ./out

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

gradient_accumulation_steps: 8
micro_batch_size: 4
num_epochs: 3
logging_steps: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 2.7e-5

wandb_project: dolphin-2.9-mixtral-8x22b
wandb_watch:
wandb_run_id:
wandb_log_model:

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

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
# resume_from_checkpoint: /home/ehartford/axolotl/out/checkpoint-316
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
saves_per_epoch: 8
save_total_limit: 2
save_steps:
evals_per_epoch: 4
eval_sample_packing: false
debug:
deepspeed: deepspeed_configs/zero3_bf16_cpuoffload_params.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
tokens:
  - "<|im_start|>"

out

This model is a fine-tuned version of mistral-community/Mixtral-8x22B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5217

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: 2.7e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 256
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 2
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
0.7022 0.0 1 0.6989
0.5344 0.25 238 0.5138
0.5204 0.5 476 0.5018
0.5059 0.75 714 0.4951
0.5112 1.0 952 0.4911
0.4561 1.24 1190 0.4978
0.478 1.49 1428 0.4935
0.4714 1.74 1666 0.4899
0.4626 1.99 1904 0.4861
0.3675 2.22 2142 0.5240
0.3595 2.47 2380 0.5229
0.3438 2.72 2618 0.5217

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.2+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0