End of training

README.md

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+
+---
+license: creativeml-openrail-m
+base_model: kerianheyi/CS245-fine-tunedSD10600_11000_14122
+datasets:
+- jytjyt05/t_to_m7
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+inference: true
+---
+    
+# Text-to-image finetuning - kerianheYi/CS245-fine-tunedSD11000_11400_14122
+
+This pipeline was finetuned from **kerianheyi/CS245-fine-tunedSD10600_11000_14122** on the **jytjyt05/t_to_m7** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A melSpectrogram for piano solo in Major']: 
+
+![val_imgs_grid](./val_imgs_grid.png)
+
+
+## Pipeline usage
+
+You can use the pipeline like so:
+
+```python
+from diffusers import DiffusionPipeline
+import torch
+
+pipeline = DiffusionPipeline.from_pretrained("kerianheYi/CS245-fine-tunedSD11000_11400_14122", torch_dtype=torch.float16)
+prompt = "A melSpectrogram for piano solo in Major"
+image = pipeline(prompt).images[0]
+image.save("my_image.png")
+```
+
+## Training info
+
+These are the key hyperparameters used during training:
+
+* Epochs: 1
+* Learning rate: 1e-05
+* Batch size: 1
+* Gradient accumulation steps: 4
+* Image resolution: 512
+* Mixed-precision: fp16
+

feature_extractor/preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 224,
+    "width": 224
+  },
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "CLIPImageProcessor",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 224
+  },
+  "use_square_size": false
+}

logs/text2image-fine-tune/1701556246.7813814/events.out.tfevents.1701556246.993071d670e8.18167.1

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logs/text2image-fine-tune/1701556246.7830482/hparams.yml

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+adam_beta1: 0.9
+adam_beta2: 0.999
+adam_epsilon: 1.0e-08
+adam_weight_decay: 0.01
+allow_tf32: false
+cache_dir: null
+caption_column: caption
+center_crop: false
+checkpointing_steps: 100000
+checkpoints_total_limit: null
+dataloader_num_workers: 0
+dataset_config_name: null
+dataset_name: jytjyt05/t_to_m7
+enable_xformers_memory_efficient_attention: false
+gradient_accumulation_steps: 4
+gradient_checkpointing: true
+hub_model_id: null
+hub_token: null
+image_column: image
+input_perturbation: 0
+learning_rate: 1.0e-05
+local_rank: -1
+logging_dir: logs
+lr_scheduler: constant
+lr_warmup_steps: 0
+max_grad_norm: 1.0
+max_train_samples: null
+max_train_steps: 400
+mixed_precision: fp16
+noise_offset: 0
+non_ema_revision: null
+num_train_epochs: 1
+output_dir: kerianheyi/CS245-fine-tunedSD11000_11400_14122
+prediction_type: null
+pretrained_model_name_or_path: kerianheyi/CS245-fine-tunedSD10600_11000_14122
+push_to_hub: true
+random_flip: false
+report_to: tensorboard
+resolution: 512
+resume_from_checkpoint: null
+revision: null
+scale_lr: false
+seed: null
+snr_gamma: null
+tracker_project_name: text2image-fine-tune
+train_batch_size: 1
+train_data_dir: null
+use_8bit_adam: false
+use_ema: true
+validation_epochs: 5
+variant: null

logs/text2image-fine-tune/events.out.tfevents.1701556246.993071d670e8.18167.0

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model_index.json

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+{
+  "_class_name": "StableDiffusionPipeline",
+  "_diffusers_version": "0.25.0.dev0",
+  "_name_or_path": "kerianheyi/CS245-fine-tunedSD10600_11000_14122",
+  "feature_extractor": [
+    "transformers",
+    "CLIPImageProcessor"
+  ],
+  "image_encoder": [
+    null,
+    null
+  ],
+  "requires_safety_checker": false,
+  "safety_checker": [
+    null,
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+  ],
+  "scheduler": [
+    "diffusers",
+    "PNDMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}

scheduler/scheduler_config.json

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+{
+  "_class_name": "PNDMScheduler",
+  "_diffusers_version": "0.25.0.dev0",
+  "beta_end": 0.012,
+  "beta_schedule": "scaled_linear",
+  "beta_start": 0.00085,
+  "clip_sample": false,
+  "num_train_timesteps": 1000,
+  "prediction_type": "epsilon",
+  "set_alpha_to_one": false,
+  "skip_prk_steps": true,
+  "steps_offset": 1,
+  "timestep_spacing": "leading",
+  "trained_betas": null
+}

text_encoder/config.json

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+{
+  "_name_or_path": "kerianheyi/CS245-fine-tunedSD10600_11000_14122",
+  "architectures": [
+    "CLIPTextModel"
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+  "attention_dropout": 0.0,
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+  "dropout": 0.0,
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+  "hidden_act": "gelu",
+  "hidden_size": 1024,
+  "initializer_factor": 1.0,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 77,
+  "model_type": "clip_text_model",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 23,
+  "pad_token_id": 1,
+  "projection_dim": 512,
+  "torch_dtype": "float16",
+  "transformers_version": "4.35.2",
+  "vocab_size": 49408
+}

text_encoder/model.safetensors

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tokenizer/special_tokens_map.json

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+  "bos_token": {
+    "content": "<|startoftext|>",
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+    "normalized": true,
+    "rstrip": false,
+    "single_word": false
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+}

tokenizer/tokenizer_config.json

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+  "add_prefix_space": false,
+  "added_tokens_decoder": {
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+      "special": true
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+  "bos_token": "<|startoftext|>",
+  "clean_up_tokenization_spaces": true,
+  "do_lower_case": true,
+  "eos_token": "<|endoftext|>",
+  "errors": "replace",
+  "model_max_length": 77,
+  "pad_token": "!",
+  "tokenizer_class": "CLIPTokenizer",
+  "unk_token": "<|endoftext|>"
+}

unet/config.json

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+{
+  "_class_name": "UNet2DConditionModel",
+  "_diffusers_version": "0.25.0.dev0",
+  "_name_or_path": "kerianheyi/CS245-fine-tunedSD10600_11000_14122",
+  "act_fn": "silu",
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vae/config.json

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