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sandernotenbaert
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okai-musiclang-content-t5-small

Transformers
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
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  1. README.md +73 -0
  2. final_model/config.json +30 -0
  3. final_model/generation_config.json +8 -0
  4. final_model/model.safetensors +3 -0
  5. final_model/special_tokens_map.json +739 -0
  6. final_model/tokenizer.json +0 -0
  7. final_model/tokenizer_config.json +955 -0
  8. final_model/training_args.bin +3 -0
  9. generation_config.json +8 -0
  10. model.safetensors +1 -1
README.md ADDED
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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: okai-musiclang-content-t5-small
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+ results: []
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+ ---
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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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+
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+ # okai-musiclang-content-t5-small
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+
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+ This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.3428
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine_with_restarts
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - lr_scheduler_warmup_steps: 500
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 3.0082 | 0.2226 | 500 | 2.8350 |
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+ | 2.3549 | 0.4452 | 1000 | 2.2682 |
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+ | 2.1648 | 0.6679 | 1500 | 2.0597 |
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+ | 2.0021 | 0.8905 | 2000 | 1.8762 |
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+ | 1.8782 | 1.1131 | 2500 | 1.7769 |
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+ | 1.7893 | 1.3357 | 3000 | 1.6655 |
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+ | 1.6761 | 1.5583 | 3500 | 1.5614 |
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+ | 1.5877 | 1.7809 | 4000 | 1.4621 |
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+ | 1.5383 | 2.0036 | 4500 | 1.4034 |
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+ | 1.5091 | 2.2262 | 5000 | 1.3646 |
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+ | 1.4742 | 2.4488 | 5500 | 1.3537 |
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+ | 1.482 | 2.6714 | 6000 | 1.3431 |
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+ | 1.4692 | 2.8940 | 6500 | 1.3428 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.54.1
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 4.0.0
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+ - Tokenizers 0.21.2
final_model/config.json ADDED
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+ {
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "classifier_dropout": 0.0,
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+ "d_ff": 512,
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+ "d_kv": 64,
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+ "d_model": 256,
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+ "decoder_start_token_id": 3,
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+ "dense_act_fn": "relu",
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 4,
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+ "feed_forward_proj": "gated-relu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "is_gated_act": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "max_position_embeddings": 8192,
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+ "model_type": "t5",
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+ "num_decoder_layers": 4,
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+ "num_heads": 4,
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+ "num_layers": 4,
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+ "pad_token_id": 1,
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+ "relative_attention_max_distance": 128,
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+ "relative_attention_num_buckets": 32,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.54.1",
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+ "use_cache": false,
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+ "vocab_size": 4896
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+ }
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