ReadyArt
/

EVA-Qwen2.5-1.5B-v0.0_EXL2_8.0bpw_H8

@@ -1,181 +1,193 @@
----
-library_name: transformers
-tags:
-- generated_from_trainer
-model-index:
-- name: EVA-Qwen2.5-1.5B-FFT-v0.0
-  results: []
-license: apache-2.0
-language:
-- en
-base_model:
-- Qwen/Qwen2.5-1.5B
-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
----
-# EVA Qwen2.5-1.5BB v0.0
-<p>
-  A small-scale RP/storywriting specialist model, full-parameter finetune of Qwen2.5-1.5B 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>
-  Unlike EVA-D 1.5B v0.0, this model was created without using DistillKit, and unlike other versions of EVA, Spectrum wasn't used either, since layer freezing is inefficient at small scale.
-</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>9 hours on 4x3090Ti</a></li></ul>
-  <h3>
-</p>
-  <p>Model was created by Kearm, Auri and Cahvay.</p>
-  <h4>Special thanks:</h4><ul>
-  <li>to Cahvay for his work on investigating and reprocessing the corrupted dataset, removing the single biggest source of data poisoning.</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: /media/kearm/Disk_2/HF_FAST_MoE_Fodder/Qwen2.5-1.5B
-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/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl
-    type: sharegpt
-  - path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl
-    type: sharegpt
-  - path: datasets/S2.jsonl
-    type: sharegpt
-  - path: datasets/Turing.jsonl
-    type: sharegpt
-chat_template: chatml
-shuffle_merged_datasets: true
-val_set_size: 0.05
-output_dir: EVA-Qwen2.5-1.5B-FFT-v0.0
-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
-wandb_project: EVA-Qwen2.5-1.5B-FFT-v0.0
-wandb_entity:
-wandb_watch:
-wandb_name: Unit-00
-wandb_log_model:
-gradient_accumulation_steps: 8
-micro_batch_size: 1
-num_epochs: 3
-optimizer: paged_adamw_8bit
-lr_scheduler: cosine
-learning_rate: 0.000005
-max_grad_norm: 1.5
-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
-save_total_limit: 8
-hub_model_id:
-hub_strategy:
-debug:
-deepspeed: deepspeed_configs/zero3_bf16.json
-weight_decay: 0.15
-# 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>

+---
+library_name: transformers
+tags:
+- generated_from_trainer
+license: apache-2.0
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-1.5B
+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
+model-index:
+- name: EVA-Qwen2.5-1.5B-FFT-v0.0
+  results: []
+---
+# EVA Qwen2.5-1.5BB v0.0
+<p>
+  A small-scale RP/storywriting specialist model, full-parameter finetune of Qwen2.5-1.5B 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>
+  Unlike EVA-D 1.5B v0.0, this model was created without using DistillKit, and unlike other versions of EVA, Spectrum wasn't used either, since layer freezing is inefficient at small scale.
+</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>9 hours on 4x3090Ti</a></li></ul>
+  <h3>
+</p>
+  <p>Model was created by Kearm, Auri and Cahvay.</p>
+  <h4>Special thanks:</h4><ul>
+  <li>to Cahvay for his work on investigating and reprocessing the corrupted dataset, removing the single biggest source of data poisoning.</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: /media/kearm/Disk_2/HF_FAST_MoE_Fodder/Qwen2.5-1.5B
+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/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl
+    type: sharegpt
+  - path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl
+    type: sharegpt
+  - path: datasets/S2.jsonl
+    type: sharegpt
+  - path: datasets/Turing.jsonl
+    type: sharegpt
+chat_template: chatml
+shuffle_merged_datasets: true
+val_set_size: 0.05
+output_dir: EVA-Qwen2.5-1.5B-FFT-v0.0
+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
+wandb_project: EVA-Qwen2.5-1.5B-FFT-v0.0
+wandb_entity:
+wandb_watch:
+wandb_name: Unit-00
+wandb_log_model:
+gradient_accumulation_steps: 8
+micro_batch_size: 1
+num_epochs: 3
+optimizer: paged_adamw_8bit
+lr_scheduler: cosine
+learning_rate: 0.000005
+max_grad_norm: 1.5
+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
+save_total_limit: 8
+hub_model_id:
+hub_strategy:
+debug:
+deepspeed: deepspeed_configs/zero3_bf16.json
+weight_decay: 0.15
+# 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>