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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: EVA-Qwen2.5-1.5B-FFT-v0.0 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.4.1` |
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```yaml |
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base_model: /media/kearm/Disk_2/HF_FAST_MoE_Fodder/Qwen2.5-1.5B |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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plugins: |
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- axolotl.integrations.liger.LigerPlugin |
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liger_rope: true |
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liger_rms_norm: true |
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liger_swiglu: true |
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liger_fused_linear_cross_entropy: true |
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# plugins: |
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# - axolotl.integrations.spectrum.SpectrumPlugin |
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# spectrum_top_fraction: 0.5 |
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# # Optional if using a pre-scanned model as your base_model. Useful if using a model mirror |
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# spectrum_model_name: Qwen/Qwen2.5-32B |
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datasets: |
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- path: datasets/Celeste_Filtered_utf8fix.jsonl |
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type: sharegpt |
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- path: datasets/deduped_not_samantha_norefusals.jsonl |
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type: sharegpt |
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- path: datasets/deduped_SynthRP-Gens_processed_ShareGPT_converted_cleaned.jsonl |
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type: sharegpt |
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- path: datasets/deduped_Synthstruct-Gens_processed_sharegpt_converted_cleaned.jsonl |
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type: sharegpt |
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- path: datasets/Gryphe-4o-WP-filtered-sharegpt_utf8fix.jsonl |
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type: sharegpt |
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- path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl |
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type: sharegpt |
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- path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl |
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type: sharegpt |
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- path: datasets/S2.jsonl |
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type: sharegpt |
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- path: datasets/Turing.jsonl |
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type: sharegpt |
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chat_template: chatml |
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shuffle_merged_datasets: true |
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val_set_size: 0.05 |
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output_dir: EVA-Qwen2.5-1.5B-FFT-v0.0 |
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sequence_len: 10240 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: true |
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# adapter: qlora |
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# lora_model_dir: |
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# lora_r: 64 |
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# lora_alpha: 128 |
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# lora_dropout: 0.05 |
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# lora_target_linear: true |
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# peft_use_dora: true |
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wandb_project: EVA-Qwen2.5-1.5B-FFT-v0.0 |
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wandb_entity: |
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wandb_watch: |
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wandb_name: Unit-00 |
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wandb_log_model: |
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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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num_epochs: 3 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000005 |
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max_grad_norm: 1.5 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: "unsloth" |
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gradient_checkpointing_kwargs: |
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use_reentrant: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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warmup_steps: 20 |
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evals_per_epoch: 4 |
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saves_per_epoch: 4 |
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save_safetensors: true |
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save_total_limit: 8 |
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hub_model_id: |
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hub_strategy: |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.15 |
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# fsdp: |
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# - full_shard |
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# - auto_wrap |
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# fsdp_config: |
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# fsdp_limit_all_gathers: true |
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# fsdp_sync_module_states: false |
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# fsdp_offload_params: true |
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# fsdp_cpu_ram_efficient_loading: true |
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# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP |
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# fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer |
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# fsdp_activation_checkpointing: true |
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# fsdp_state_dict_type: SHARDED_STATE_DICT # Changed from FULL_STATE_DICT |
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# fsdp_sharding_strategy: FULL_SHARD |
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# fsdp_forward_prefetch: false # Added |
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# fsdp_backward_prefetch: "BACKWARD_PRE" # Added |
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# fsdp_backward_prefetch_limit: 1 # Added |
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# fsdp_mixed_precision: BF16 # Added |
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``` |
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</details><br> |
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# EVA-Qwen2.5-1.5B-FFT-v0.0 |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3685 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 4 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.8166 | 0.0028 | 1 | 1.6772 | |
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| 1.7031 | 0.2519 | 89 | 1.4633 | |
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| 1.5925 | 0.5037 | 178 | 1.4171 | |
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| 1.512 | 0.7556 | 267 | 1.3993 | |
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| 1.5122 | 1.0050 | 356 | 1.3888 | |
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| 1.5281 | 1.2574 | 445 | 1.3825 | |
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| 1.4895 | 1.5099 | 534 | 1.3775 | |
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| 1.4599 | 1.7624 | 623 | 1.3731 | |
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| 1.4754 | 2.0103 | 712 | 1.3705 | |
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| 1.4841 | 2.2619 | 801 | 1.3696 | |
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| 1.4861 | 2.5136 | 890 | 1.3689 | |
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| 1.5258 | 2.7653 | 979 | 1.3685 | |
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### Framework versions |
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- Transformers 4.45.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 2.21.0 |
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- Tokenizers 0.20.3 |
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