Hugging Face's logo

EVA-UNIT-01
/
EVA-Qwen2.5-14B-v0.2

Text Generation
Transformers
Safetensors
qwen2
Generated from Trainer
conversational
text-generation-inference
Inference Endpoints
Model card Files Community
1
EVA-Qwen2.5-14B-v0.2 / README.md
Kearm's picture
Kearm
Upload folder using huggingface_hub
669ae9e verified
preview code
|
raw
history blame
12.4 kB
metadata
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-14B
tags:
  - generated_from_trainer
model-index:
  - name: EVA-Qwen2.5-14B-SFFT-v0.2
    results: []

Built with Axolotl

See axolotl config

axolotl version: 0.4.1

base_model: Qwen/Qwen2.5-14B

load_in_8bit: false
load_in_4bit: false
strict: false

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true

# plugins:
#   - axolotl.integrations.spectrum.SpectrumPlugin

# spectrum_top_fraction: 0.5
# # Optional if using a pre-scanned model as your base_model. Useful if using a model mirror
# spectrum_model_name: Qwen/Qwen2.5-32B

datasets:
  - path: datasets/Celeste_Filtered_utf8fix.jsonl
    type: sharegpt
  - path: datasets/deduped_not_samantha_norefusals.jsonl
    type: sharegpt
  - path: datasets/deduped_SynthRP-Gens_processed_ShareGPT_converted_cleaned.jsonl
    type: sharegpt
  - path: datasets/deduped_Synthstruct-Gens_processed_sharegpt_converted_cleaned.jsonl
    type: sharegpt
  - path: datasets/Gryphe-4o-WP-filtered-sharegpt_utf8fix.jsonl
    type: sharegpt
  - path: datasets/opus-instruct-22k-no_refusals-filtered_utf8fix.jsonl
    type: sharegpt
  - path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl
    type: sharegpt
  - path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl
    type: sharegpt

chat_template: chatml
shuffle_merged_datasets: true
val_set_size: 0.001
output_dir: ./EVA-Qwen2.5-14B-SFFT-v0.2

sequence_len: 10240
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

# adapter: qlora
# lora_model_dir:
# lora_r: 64
# lora_alpha: 128
# lora_dropout: 0.05
# lora_target_linear: true
# peft_use_dora: true

base_model: Qwen/Qwen2.5-14B

load_in_8bit: false
load_in_4bit: false
strict: false

plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true

datasets:
  - path: datasets/Celeste_Filtered_utf8fix.jsonl
    type: sharegpt
  - path: datasets/deduped_not_samantha_norefusals.jsonl
    type: sharegpt
  - path: datasets/deduped_SynthRP-Gens_processed_ShareGPT_converted_cleaned.jsonl
    type: sharegpt
  - path: datasets/deduped_Synthstruct-Gens_processed_sharegpt_converted_cleaned.jsonl
    type: sharegpt
  - path: datasets/Gryphe-4o-WP-filtered-sharegpt_utf8fix.jsonl
    type: sharegpt
  - path: datasets/opus-instruct-22k-no_refusals-filtered_utf8fix.jsonl
    type: sharegpt
  - path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl
    type: sharegpt
  - path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl
    type: sharegpt

chat_template: chatml
shuffle_merged_datasets: true
val_set_size: 0.005
output_dir: ./EVA-Qwen2.5-14B-SFFT-v0.2

sequence_len: 10240
sample_packing: true
eval_sample_packing: false
pad_to_sequence_len: true

# adapter: qlora
# lora_model_dir:
# lora_r: 32
# lora_alpha: 16
# lora_dropout: 0.05
# lora_target_linear: true
# peft_use_dora: true

unfrozen_parameters:
- ^lm_head.weight$
- ^model.embed_tokens.weight$
# mlp.down_proj layers
- model.layers.1.mlp.down_proj
- model.layers.35.mlp.down_proj
- model.layers.38.mlp.down_proj
- model.layers.37.mlp.down_proj
- model.layers.36.mlp.down_proj
- model.layers.15.mlp.down_proj
- model.layers.11.mlp.down_proj
- model.layers.12.mlp.down_proj
- model.layers.34.mlp.down_proj
- model.layers.44.mlp.down_proj
- model.layers.45.mlp.down_proj
- model.layers.9.mlp.down_proj
- model.layers.41.mlp.down_proj
- model.layers.33.mlp.down_proj
- model.layers.43.mlp.down_proj
- model.layers.40.mlp.down_proj
- model.layers.13.mlp.down_proj
- model.layers.8.mlp.down_proj
- model.layers.39.mlp.down_proj
- model.layers.10.mlp.down_proj
- model.layers.14.mlp.down_proj
- model.layers.16.mlp.down_proj
- model.layers.31.mlp.down_proj
- model.layers.32.mlp.down_proj
# mlp.gate_proj layers
- model.layers.1.mlp.gate_proj
- model.layers.44.mlp.gate_proj
- model.layers.46.mlp.gate_proj
- model.layers.45.mlp.gate_proj
- model.layers.43.mlp.gate_proj
- model.layers.47.mlp.gate_proj
- model.layers.42.mlp.gate_proj
- model.layers.32.mlp.gate_proj
- model.layers.27.mlp.gate_proj
- model.layers.33.mlp.gate_proj
- model.layers.28.mlp.gate_proj
- model.layers.39.mlp.gate_proj
- model.layers.41.mlp.gate_proj
- model.layers.40.mlp.gate_proj
- model.layers.30.mlp.gate_proj
- model.layers.29.mlp.gate_proj
- model.layers.31.mlp.gate_proj
- model.layers.37.mlp.gate_proj
- model.layers.26.mlp.gate_proj
- model.layers.10.mlp.gate_proj
- model.layers.38.mlp.gate_proj
- model.layers.36.mlp.gate_proj
- model.layers.12.mlp.gate_proj
- model.layers.13.mlp.gate_proj
# mlp.up_proj layers
- model.layers.1.mlp.up_proj
- model.layers.13.mlp.up_proj
- model.layers.11.mlp.up_proj
- model.layers.14.mlp.up_proj
- model.layers.15.mlp.up_proj
- model.layers.12.mlp.up_proj
- model.layers.8.mlp.up_proj
- model.layers.16.mlp.up_proj
- model.layers.9.mlp.up_proj
- model.layers.19.mlp.up_proj
- model.layers.10.mlp.up_proj
- model.layers.7.mlp.up_proj
- model.layers.17.mlp.up_proj
- model.layers.20.mlp.up_proj
- model.layers.21.mlp.up_proj
- model.layers.18.mlp.up_proj
- model.layers.37.mlp.up_proj
- model.layers.38.mlp.up_proj
- model.layers.39.mlp.up_proj
- model.layers.42.mlp.up_proj
- model.layers.41.mlp.up_proj
- model.layers.27.mlp.up_proj
- model.layers.28.mlp.up_proj
- model.layers.36.mlp.up_proj
# self_attn.k_proj layers
- model.layers.47.self_attn.k_proj
- model.layers.39.self_attn.k_proj
- model.layers.41.self_attn.k_proj
- model.layers.37.self_attn.k_proj
- model.layers.35.self_attn.k_proj
- model.layers.44.self_attn.k_proj
- model.layers.38.self_attn.k_proj
- model.layers.14.self_attn.k_proj
- model.layers.7.self_attn.k_proj
- model.layers.12.self_attn.k_proj
- model.layers.11.self_attn.k_proj
- model.layers.32.self_attn.k_proj
- model.layers.10.self_attn.k_proj
- model.layers.8.self_attn.k_proj
- model.layers.6.self_attn.k_proj
- model.layers.9.self_attn.k_proj
- model.layers.45.self_attn.k_proj
- model.layers.42.self_attn.k_proj
- model.layers.40.self_attn.k_proj
- model.layers.5.self_attn.k_proj
- model.layers.0.self_attn.k_proj
- model.layers.33.self_attn.k_proj
- model.layers.34.self_attn.k_proj
- model.layers.13.self_attn.k_proj
# self_attn.o_proj layers
- model.layers.12.self_attn.o_proj
- model.layers.5.self_attn.o_proj
- model.layers.14.self_attn.o_proj
- model.layers.16.self_attn.o_proj
- model.layers.20.self_attn.o_proj
- model.layers.13.self_attn.o_proj
- model.layers.11.self_attn.o_proj
- model.layers.4.self_attn.o_proj
- model.layers.6.self_attn.o_proj
- model.layers.19.self_attn.o_proj
- model.layers.7.self_attn.o_proj
- model.layers.18.self_attn.o_proj
- model.layers.8.self_attn.o_proj
- model.layers.38.self_attn.o_proj
- model.layers.15.self_attn.o_proj
- model.layers.17.self_attn.o_proj
- model.layers.9.self_attn.o_proj
- model.layers.10.self_attn.o_proj
- model.layers.21.self_attn.o_proj
- model.layers.28.self_attn.o_proj
- model.layers.32.self_attn.o_proj
- model.layers.35.self_attn.o_proj
- model.layers.39.self_attn.o_proj
- model.layers.3.self_attn.o_proj
# self_attn.q_proj layers
- model.layers.1.self_attn.q_proj
- model.layers.2.self_attn.q_proj
- model.layers.3.self_attn.q_proj
- model.layers.44.self_attn.q_proj
- model.layers.29.self_attn.q_proj
- model.layers.45.self_attn.q_proj
- model.layers.43.self_attn.q_proj
- model.layers.32.self_attn.q_proj
- model.layers.38.self_attn.q_proj
- model.layers.19.self_attn.q_proj
- model.layers.42.self_attn.q_proj
- model.layers.34.self_attn.q_proj
- model.layers.36.self_attn.q_proj
- model.layers.40.self_attn.q_proj
- model.layers.26.self_attn.q_proj
- model.layers.20.self_attn.q_proj
- model.layers.28.self_attn.q_proj
- model.layers.39.self_attn.q_proj
- model.layers.41.self_attn.q_proj
- model.layers.33.self_attn.q_proj
- model.layers.35.self_attn.q_proj
- model.layers.25.self_attn.q_proj
- model.layers.30.self_attn.q_proj
- model.layers.27.self_attn.q_proj
# self_attn.v_proj layers
- model.layers.0.self_attn.v_proj
- model.layers.7.self_attn.v_proj
- model.layers.39.self_attn.v_proj
- model.layers.31.self_attn.v_proj
- model.layers.15.self_attn.v_proj
- model.layers.10.self_attn.v_proj
- model.layers.41.self_attn.v_proj
- model.layers.32.self_attn.v_proj
- model.layers.6.self_attn.v_proj
- model.layers.33.self_attn.v_proj
- model.layers.42.self_attn.v_proj
- model.layers.29.self_attn.v_proj
- model.layers.9.self_attn.v_proj
- model.layers.14.self_attn.v_proj
- model.layers.35.self_attn.v_proj
- model.layers.38.self_attn.v_proj
- model.layers.13.self_attn.v_proj
- model.layers.30.self_attn.v_proj
- model.layers.34.self_attn.v_proj
- model.layers.5.self_attn.v_proj
- model.layers.28.self_attn.v_proj
- model.layers.37.self_attn.v_proj
- model.layers.27.self_attn.v_proj
- model.layers.11.self_attn.v_proj

wandb_project: EVA-Qwen2.5-14B-SFFT-v0.2
wandb_entity:
wandb_watch:
wandb_name: Unit-02
wandb_log_model:

gradient_accumulation_steps: 8
micro_batch_size: 2
num_epochs: 3
optimizer: paged_ademamix_8bit
lr_scheduler: cosine
learning_rate: 0.00005
max_grad_norm: 3

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

gradient_checkpointing: "unsloth"
# gradient_checkpointing_kwargs:
#   use_reentrant: true
early_stopping_patience:
resume_from_checkpoint: 
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 20
evals_per_epoch: 4
saves_per_epoch: 4
save_safetensors: true
hub_model_id: 
hub_strategy: 
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.1
# fsdp:
#   - full_shard
#   - auto_wrap
# fsdp_config:
#   fsdp_limit_all_gathers: true
#   fsdp_sync_module_states: false
#   fsdp_offload_params: true
#   fsdp_cpu_ram_efficient_loading: true
#   fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
#   fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer
#   fsdp_activation_checkpointing: true
#   fsdp_state_dict_type: SHARDED_STATE_DICT  # Changed from FULL_STATE_DICT
#   fsdp_sharding_strategy: FULL_SHARD
#   fsdp_forward_prefetch: false  # Added
#   fsdp_backward_prefetch: "BACKWARD_PRE"  # Added
#   fsdp_backward_prefetch_limit: 1  # Added
#   fsdp_mixed_precision: BF16  # Added

EVA-Qwen2.5-14B-SFFT-v0.2

This model is a fine-tuned version of Qwen/Qwen2.5-14B on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 3.0986

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: 5e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 20
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
1.4236 0.0170 1 2.6557
1.2513 0.2553 15 3.4606
1.1338 0.5106 30 3.5536
1.0985 0.7660 45 3.1957
0.8794 1.0170 60 3.0346
0.8584 1.2718 75 3.0551
0.8421 1.5265 90 3.0168
0.8081 1.7813 105 3.0335
0.8227 2.0361 120 3.0369
0.7416 2.2909 135 3.0876
0.7396 2.5456 150 3.1023
0.7775 2.8004 165 3.0986

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.20.2