Upload folder using huggingface_hub

README.md

@@ -0,0 +1,492 @@
+---
+library_name: transformers
+license: other
+license_name: qwen
+license_link: https://huggingface.co/Qwen/Qwen2.5-72B-Instruct/blob/main/LICENSE
+base_model: Qwen/Qwen2.5-72B
+datasets:
+- anthracite-org/kalo-opus-instruct-22k-no-refusal
+- Nopm/Opus_WritingStruct
+- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned
+- Gryphe/Sonnet3.5-Charcard-Roleplay
+- Gryphe/ChatGPT-4o-Writing-Prompts
+- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
+- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
+- nothingiisreal/Reddit-Dirty-And-WritingPrompts
+- allura-org/Celeste-1.x-data-mixture
+- cognitivecomputations/dolphin-2.9.3
+tags:
+- generated_from_trainer
+model-index:
+- name: EVA-Qwen2.5-72B-SFFT-v0.1
+  results: []
+---
+
+# This repo contains the copy of the original quantized to INT8. Original: [EVA-UNIT-01/EVA-Qwen2.5-72B-v0.1](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-72B-v0.1)
+
+# EVA Qwen2.5-72B v0.1
+
+<p>
+  A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-72B on mixture of synthetic and natural data.<br>
+  It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model.<br>
+</p>
+
+<p>Dedicated to Nev.</p>
+
+<p><b>Version notes for 0.1</b>: Reprocessed dataset (via Cahvay for 32B 0.2, used here as well), readjusted training config for 8xH100 SXM. Significant improvements in instruction following, long context understanding and overall coherence over v0.0.</p>
+
+<p>
+  <p>Prompt format is ChatML.</p><br>
+  <h3>Recommended sampler values:</h3>
+  <ul>
+  <li>Temperature: 1</li>
+  <li>Min-P: 0.05</li>
+  <li>Top-A: 0.2</li>
+  <li>Repetition Penalty: 1.03</li>
+  </ul>
+  
+  <h3>Recommended SillyTavern presets (via CalamitousFelicitousness):</h3>
+
+  - [Context](https://huggingface.co/EVA-UNIT-01/EVA-Yi-1.5-9B-32K-V1/blob/main/%5BChatML%5D%20Roleplay-v1.9%20Context.json)
+  - [Instruct and System Prompt](https://huggingface.co/EVA-UNIT-01/EVA-Yi-1.5-9B-32K-V1/blob/main/%5BChatML%5D%20Roleplay-v1.9%20Instruct.json)
+</p>
+
+<p>
+  <br>
+  <h3>
+    Training data:
+  </h3>
+    <ul>
+      <li>Celeste 70B 0.1 data mixture minus Opus Instruct subset. See that model's <a href=https://huggingface.co/nothingiisreal/L3.1-70B-Celeste-V0.1-BF16>card</a> for details.</li>
+      <li>Kalomaze's Opus_Instruct_25k dataset, filtered for refusals.</li>
+      <li>A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe</li>
+      <li>A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe</li>
+      <li>Synthstruct and SynthRP datasets by Epiculous</li>
+      <li>A subset from Dolphin-2.9.3, including filtered version of not_samantha and a small subset of systemchat.</li>
+    </ul>
+  <h3>
+     Training time and hardware:
+  </h3>
+      <ul><li>15 hours on 8xH100 SXM, provided by <a href=https://featherless.ai/>FeatherlessAI</a></li></ul><br>
+</p>
+  <p>Model was created by Kearm, Auri and Cahvay.</p>
+  <h4>Special thanks:</h4><ul>
+  <li><b>to Cahvay for his work on investigating and reprocessing the corrupted dataset, removing the single biggest source of data poisoning.</b></li>
+  <li><b>to <a href=https://featherless.ai/>FeatherlessAI</a> for generously providing 8xH100 SXM node for training of this model</b></li>
+  <li>to Gryphe, Lemmy, Kalomaze, Nopm, Epiculous and CognitiveComputations for the data</li>
+  <li>and to Allura-org for support, feedback, beta-testing and doing quality control of EVA models.</li></ul>
+
+
+[<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)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+base_model: Qwen/Qwen2.5-72B
+
+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-Qwen2.5-72B-SFFT-v0.1
+
+sequence_len: 8192
+sample_packing: true
+eval_sample_packing: false
+pad_to_sequence_len: false
+
+# adapter: qlora
+# lora_model_dir:
+# lora_r: 64
+# lora_alpha: 128
+# 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.62.mlp.down_proj
+- model.layers.64.mlp.down_proj
+- model.layers.63.mlp.down_proj
+- model.layers.66.mlp.down_proj
+- model.layers.65.mlp.down_proj
+- model.layers.67.mlp.down_proj
+- model.layers.68.mlp.down_proj
+- model.layers.31.mlp.down_proj
+- model.layers.60.mlp.down_proj
+- model.layers.69.mlp.down_proj
+- model.layers.61.mlp.down_proj
+- model.layers.59.mlp.down_proj
+- model.layers.30.mlp.down_proj
+- model.layers.70.mlp.down_proj
+- model.layers.32.mlp.down_proj
+- model.layers.34.mlp.down_proj
+- model.layers.33.mlp.down_proj
+- model.layers.76.mlp.down_proj
+- model.layers.72.mlp.down_proj
+- model.layers.71.mlp.down_proj
+- model.layers.58.mlp.down_proj
+- model.layers.75.mlp.down_proj
+- model.layers.29.mlp.down_proj
+- model.layers.56.mlp.down_proj
+- model.layers.26.mlp.down_proj
+- model.layers.35.mlp.down_proj
+- model.layers.28.mlp.down_proj
+- model.layers.57.mlp.down_proj
+- model.layers.77.mlp.down_proj
+- model.layers.36.mlp.down_proj
+- model.layers.27.mlp.down_proj
+- model.layers.25.mlp.down_proj
+- model.layers.78.mlp.down_proj
+- model.layers.37.mlp.down_proj
+- model.layers.73.mlp.down_proj
+- model.layers.55.mlp.down_proj
+- model.layers.54.mlp.down_proj
+- model.layers.74.mlp.down_proj
+- model.layers.24.mlp.down_proj
+- model.layers.53.mlp.down_proj
+# mlp.gate_proj layers
+- model.layers.78.mlp.gate_proj
+- model.layers.77.mlp.gate_proj
+- model.layers.76.mlp.gate_proj
+- model.layers.79.mlp.gate_proj
+- model.layers.75.mlp.gate_proj
+- model.layers.74.mlp.gate_proj
+- model.layers.73.mlp.gate_proj
+- model.layers.72.mlp.gate_proj
+- model.layers.71.mlp.gate_proj
+- model.layers.70.mlp.gate_proj
+- model.layers.69.mlp.gate_proj
+- model.layers.57.mlp.gate_proj
+- model.layers.54.mlp.gate_proj
+- model.layers.55.mlp.gate_proj
+- model.layers.68.mlp.gate_proj
+- model.layers.63.mlp.gate_proj
+- model.layers.53.mlp.gate_proj
+- model.layers.44.mlp.gate_proj
+- model.layers.45.mlp.gate_proj
+- model.layers.49.mlp.gate_proj
+- model.layers.58.mlp.gate_proj
+- model.layers.46.mlp.gate_proj
+- model.layers.56.mlp.gate_proj
+- model.layers.67.mlp.gate_proj
+- model.layers.62.mlp.gate_proj
+- model.layers.50.mlp.gate_proj
+- model.layers.64.mlp.gate_proj
+- model.layers.52.mlp.gate_proj
+- model.layers.40.mlp.gate_proj
+- model.layers.43.mlp.gate_proj
+- model.layers.48.mlp.gate_proj
+- model.layers.66.mlp.gate_proj
+- model.layers.47.mlp.gate_proj
+- model.layers.59.mlp.gate_proj
+- model.layers.65.mlp.gate_proj
+- model.layers.61.mlp.gate_proj
+- model.layers.60.mlp.gate_proj
+- model.layers.42.mlp.gate_proj
+- model.layers.51.mlp.gate_proj
+- model.layers.41.mlp.gate_proj
+# mlp.up_proj layers
+- model.layers.70.mlp.up_proj
+- model.layers.69.mlp.up_proj
+- model.layers.71.mlp.up_proj
+- model.layers.68.mlp.up_proj
+- model.layers.72.mlp.up_proj
+- model.layers.67.mlp.up_proj
+- model.layers.66.mlp.up_proj
+- model.layers.73.mlp.up_proj
+- model.layers.46.mlp.up_proj
+- model.layers.63.mlp.up_proj
+- model.layers.75.mlp.up_proj
+- model.layers.76.mlp.up_proj
+- model.layers.74.mlp.up_proj
+- model.layers.45.mlp.up_proj
+- model.layers.62.mlp.up_proj
+- model.layers.64.mlp.up_proj
+- model.layers.65.mlp.up_proj
+- model.layers.44.mlp.up_proj
+- model.layers.53.mlp.up_proj
+- model.layers.47.mlp.up_proj
+- model.layers.49.mlp.up_proj
+- model.layers.48.mlp.up_proj
+- model.layers.57.mlp.up_proj
+- model.layers.43.mlp.up_proj
+- model.layers.42.mlp.up_proj
+- model.layers.56.mlp.up_proj
+- model.layers.61.mlp.up_proj
+- model.layers.54.mlp.up_proj
+- model.layers.40.mlp.up_proj
+- model.layers.55.mlp.up_proj
+- model.layers.77.mlp.up_proj
+- model.layers.60.mlp.up_proj
+- model.layers.41.mlp.up_proj
+- model.layers.35.mlp.up_proj
+- model.layers.37.mlp.up_proj
+- model.layers.58.mlp.up_proj
+- model.layers.34.mlp.up_proj
+- model.layers.38.mlp.up_proj
+- model.layers.33.mlp.up_proj
+- model.layers.39.mlp.up_proj
+# self_attn.k_proj layers
+- model.layers.36.self_attn.k_proj
+- model.layers.79.self_attn.k_proj
+- model.layers.35.self_attn.k_proj
+- model.layers.34.self_attn.k_proj
+- model.layers.37.self_attn.k_proj
+- model.layers.33.self_attn.k_proj
+- model.layers.38.self_attn.k_proj
+- model.layers.39.self_attn.k_proj
+- model.layers.74.self_attn.k_proj
+- model.layers.77.self_attn.k_proj
+- model.layers.41.self_attn.k_proj
+- model.layers.69.self_attn.k_proj
+- model.layers.32.self_attn.k_proj
+- model.layers.78.self_attn.k_proj
+- model.layers.30.self_attn.k_proj
+- model.layers.70.self_attn.k_proj
+- model.layers.25.self_attn.k_proj
+- model.layers.42.self_attn.k_proj
+- model.layers.29.self_attn.k_proj
+- model.layers.31.self_attn.k_proj
+- model.layers.68.self_attn.k_proj
+- model.layers.66.self_attn.k_proj
+- model.layers.22.self_attn.k_proj
+- model.layers.65.self_attn.k_proj
+- model.layers.44.self_attn.k_proj
+- model.layers.40.self_attn.k_proj
+- model.layers.63.self_attn.k_proj
+- model.layers.23.self_attn.k_proj
+- model.layers.28.self_attn.k_proj
+- model.layers.24.self_attn.k_proj
+- model.layers.26.self_attn.k_proj
+- model.layers.67.self_attn.k_proj
+- model.layers.75.self_attn.k_proj
+- model.layers.27.self_attn.k_proj
+- model.layers.57.self_attn.k_proj
+- model.layers.64.self_attn.k_proj
+- model.layers.71.self_attn.k_proj
+- model.layers.61.self_attn.k_proj
+- model.layers.72.self_attn.k_proj
+- model.layers.73.self_attn.k_proj
+# self_attn.o_proj layers
+- model.layers.69.self_attn.o_proj
+- model.layers.39.self_attn.o_proj
+- model.layers.16.self_attn.o_proj
+- model.layers.14.self_attn.o_proj
+- model.layers.19.self_attn.o_proj
+- model.layers.42.self_attn.o_proj
+- model.layers.12.self_attn.o_proj
+- model.layers.15.self_attn.o_proj
+- model.layers.17.self_attn.o_proj
+- model.layers.38.self_attn.o_proj
+- model.layers.23.self_attn.o_proj
+- model.layers.22.self_attn.o_proj
+- model.layers.13.self_attn.o_proj
+- model.layers.29.self_attn.o_proj
+- model.layers.41.self_attn.o_proj
+- model.layers.44.self_attn.o_proj
+- model.layers.46.self_attn.o_proj
+- model.layers.45.self_attn.o_proj
+- model.layers.43.self_attn.o_proj
+- model.layers.49.self_attn.o_proj
+- model.layers.30.self_attn.o_proj
+- model.layers.26.self_attn.o_proj
+- model.layers.25.self_attn.o_proj
+- model.layers.37.self_attn.o_proj
+- model.layers.47.self_attn.o_proj
+- model.layers.11.self_attn.o_proj
+- model.layers.18.self_attn.o_proj
+- model.layers.28.self_attn.o_proj
+- model.layers.20.self_attn.o_proj
+- model.layers.27.self_attn.o_proj
+- model.layers.53.self_attn.o_proj
+- model.layers.52.self_attn.o_proj
+- model.layers.35.self_attn.o_proj
+- model.layers.71.self_attn.o_proj
+- model.layers.10.self_attn.o_proj
+- model.layers.3.self_attn.o_proj
+- model.layers.21.self_attn.o_proj
+- model.layers.24.self_attn.o_proj
+- model.layers.68.self_attn.o_proj
+- model.layers.48.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.0.self_attn.q_proj
+- model.layers.5.self_attn.q_proj
+- model.layers.4.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.9.self_attn.q_proj
+- model.layers.10.self_attn.q_proj
+- model.layers.68.self_attn.q_proj
+- model.layers.25.self_attn.q_proj
+- model.layers.12.self_attn.q_proj
+- model.layers.54.self_attn.q_proj
+- model.layers.55.self_attn.q_proj
+- model.layers.61.self_attn.q_proj
+- model.layers.18.self_attn.q_proj
+- model.layers.49.self_attn.q_proj
+- model.layers.66.self_attn.q_proj
+- model.layers.72.self_attn.q_proj
+- model.layers.11.self_attn.q_proj
+- model.layers.52.self_attn.q_proj
+- model.layers.64.self_attn.q_proj
+- model.layers.15.self_attn.q_proj
+- model.layers.60.self_attn.q_proj
+- model.layers.50.self_attn.q_proj
+- model.layers.59.self_attn.q_proj
+- model.layers.53.self_attn.q_proj
+- model.layers.48.self_attn.q_proj
+- model.layers.57.self_attn.q_proj
+- model.layers.70.self_attn.q_proj
+- model.layers.17.self_attn.q_proj
+- model.layers.67.self_attn.q_proj
+- model.layers.71.self_attn.q_proj
+- model.layers.62.self_attn.q_proj
+- model.layers.51.self_attn.q_proj
+- model.layers.19.self_attn.q_proj
+- model.layers.58.self_attn.q_proj
+- model.layers.13.self_attn.q_proj
+# self_attn.v_proj layers
+- model.layers.23.self_attn.v_proj
+- model.layers.25.self_attn.v_proj
+- model.layers.26.self_attn.v_proj
+- model.layers.27.self_attn.v_proj
+- model.layers.28.self_attn.v_proj
+- model.layers.29.self_attn.v_proj
+- model.layers.30.self_attn.v_proj
+- model.layers.31.self_attn.v_proj
+- model.layers.34.self_attn.v_proj
+- model.layers.35.self_attn.v_proj
+- model.layers.36.self_attn.v_proj
+- model.layers.37.self_attn.v_proj
+- model.layers.38.self_attn.v_proj
+- model.layers.42.self_attn.v_proj
+- model.layers.48.self_attn.v_proj
+- model.layers.57.self_attn.v_proj
+- model.layers.58.self_attn.v_proj
+- model.layers.61.self_attn.v_proj
+- model.layers.63.self_attn.v_proj
+- model.layers.64.self_attn.v_proj
+- model.layers.65.self_attn.v_proj
+- model.layers.66.self_attn.v_proj
+- model.layers.69.self_attn.v_proj
+- model.layers.70.self_attn.v_proj
+- model.layers.74.self_attn.v_proj
+- model.layers.75.self_attn.v_proj
+- model.layers.72.self_attn.v_proj
+- model.layers.39.self_attn.v_proj
+- model.layers.41.self_attn.v_proj
+- model.layers.40.self_attn.v_proj
+- model.layers.33.self_attn.v_proj
+- model.layers.59.self_attn.v_proj
+- model.layers.16.self_attn.v_proj
+- model.layers.15.self_attn.v_proj
+- model.layers.76.self_attn.v_proj
+- model.layers.24.self_attn.v_proj
+- model.layers.68.self_attn.v_proj
+- model.layers.67.self_attn.v_proj
+- model.layers.55.self_attn.v_proj
+- model.layers.44.self_attn.v_proj
+
+
+
+wandb_project: EVA-Qwen2.5-72B-SFFT-v0.1
+wandb_entity:
+wandb_watch:
+wandb_name: Unit-01
+wandb_log_model:
+
+gradient_accumulation_steps: 8
+micro_batch_size: 1
+num_epochs: 3
+optimizer: paged_adamw_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_cpuoffload_params.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
+```
+
+</details><br>