End of training
Browse files- .gitignore +1 -0
- README.md +63 -0
- config.json +33 -0
- pytorch_model.bin +3 -0
- runs/Sep27_13-26-15_9d0c362fbcb9/1664285199.2157762/events.out.tfevents.1664285199.9d0c362fbcb9.68.1 +3 -0
- runs/Sep27_13-26-15_9d0c362fbcb9/events.out.tfevents.1664285199.9d0c362fbcb9.68.0 +3 -0
- runs/Sep27_13-26-15_9d0c362fbcb9/events.out.tfevents.1664286474.9d0c362fbcb9.68.2 +3 -0
- training_args.bin +3 -0
.gitignore
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checkpoint-*/
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README.md
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---
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license: bigscience-bloom-rail-1.0
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tags:
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- generated_from_trainer
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model-index:
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- name: bloom-560m-finetuned-common_gen
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results: []
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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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# bloom-560m-finetuned-common_gen
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This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3937
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 4
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.4819 | 0.38 | 100 | 1.4582 |
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| 1.2451 | 0.76 | 200 | 1.4247 |
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| 1.1016 | 1.14 | 300 | 1.4382 |
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| 0.9724 | 1.53 | 400 | 1.4207 |
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| 0.9396 | 1.91 | 500 | 1.3949 |
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### Framework versions
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- Transformers 4.22.1
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- Pytorch 1.12.1+cu113
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- Datasets 2.5.1
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- Tokenizers 0.12.1
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config.json
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{
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"_name_or_path": "bigscience/bloom-560m",
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"apply_residual_connection_post_layernorm": false,
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"architectures": [
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"BloomForCausalLM"
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],
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"attention_dropout": 0.0,
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"attention_softmax_in_fp32": true,
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"bias_dropout_fusion": true,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_dropout": 0.0,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"masked_softmax_fusion": true,
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"model_type": "bloom",
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"n_head": 16,
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"n_inner": null,
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"n_layer": 24,
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"offset_alibi": 100,
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"pad_token_id": 3,
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"pretraining_tp": 1,
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"seq_length": 2048,
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"skip_bias_add": true,
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"skip_bias_add_qkv": false,
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"slow_but_exact": false,
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"torch_dtype": "float32",
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"transformers_version": "4.22.1",
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"unk_token_id": 0,
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"use_cache": false,
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"vocab_size": 250880
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}
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pytorch_model.bin
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