Update README.md

README.md

@@ -1,7 +1,9 @@
 ---
 library_name: transformers
 license: apache-2.0
-base_model: EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
+base_model:
+- EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2
+- Qwen/Qwen2.5-14B
 datasets:
 - anthracite-org/kalo-opus-instruct-22k-no-refusal
 - Nopm/Opus_WritingStruct
@@ -26,6 +28,398 @@ model-index:
 This model was converted to GGUF format from [`EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2`](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
 Refer to the [original model card](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) for more details on the model.
 
+---
+Model details:
+-
+ A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-14B on mixture of synthetic and natural data.
+It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model.
+
+Version notes for 0.2: Now using the refined dataset from 32B 0.2. Major improvements in coherence, instruction following and long-context comprehension over 14B v0.1.
+
+Prompt format is ChatML.
+
+Recommended sampler values:
+
+    Temperature: 0.8
+    Min-P: 0.05
+    Top-A: 0.3
+    Repetition Penalty: 1.03
+
+Recommended SillyTavern presets (via CalamitousFelicitousness):
+
+    Context
+    Instruct and System Prompt
+
+
+Training data:
+
+    Celeste 70B 0.1 data mixture minus Opus Instruct subset. See that model's card for details.
+    Kalomaze's Opus_Instruct_25k dataset, filtered for refusals.
+    A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe
+    A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe
+    Synthstruct and SynthRP datasets by Epiculous
+    A subset from Dolphin-2.9.3, including filtered version of not_samantha and a small subset of systemchat.
+
+Training time and hardware:
+
+    3 hours on 8xH100 SXM, provided by FeatherlessAI
+
+
+Model was created by Kearm, Auri and Cahvay.
+Special thanks:
+
+    to Cahvay for his work on investigating and reprocessing the corrupted dataset, removing the single biggest source of data poisoning.
+    to FeatherlessAI for generously providing 8xH100 SXM node for training of this model
+    to Gryphe, Lemmy, Kalomaze, Nopm, Epiculous and CogninitiveComputations for the data
+    and to Allura-org for support, feedback, beta-testing and doing quality control of EVA models.
+
+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
+
+---
 ## Use with llama.cpp
 Install llama.cpp through brew (works on Mac and Linux)
 
@@ -64,4 +458,4 @@ Step 3: Run inference through the main binary.
 or 
 ```
 ./llama-server --hf-repo Triangle104/EVA-Qwen2.5-14B-v0.2-Q8_0-GGUF --hf-file eva-qwen2.5-14b-v0.2-q8_0.gguf -c 2048
-```
+```