End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,70 @@
+---
+base_model: bigscience/bloom-560m
+datasets:
+- scitldr
+library_name: peft
+license: bigscience-bloom-rail-1.0
+tags:
+- trl
+- sft
+- generated_from_trainer
+model-index:
+- name: Summarization-Bloom560m
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# Summarization-Bloom560m
+
+This model is a fine-tuned version of [bigscience/bloom-560m](https://huggingface.co/bigscience/bloom-560m) on the scitldr dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.8578
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.8487        | 0.2510 | 500  | 2.9019          |
+| 2.8069        | 0.5020 | 1000 | 2.8799          |
+| 2.8195        | 0.7530 | 1500 | 2.8660          |
+| 2.8024        | 1.0040 | 2000 | 2.8556          |
+| 2.661         | 1.2550 | 2500 | 2.8637          |
+| 2.6136        | 1.5060 | 3000 | 2.8608          |
+| 2.5816        | 1.7570 | 3500 | 2.8578          |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

adapter_config.json

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+  "base_model_name_or_path": "bigscience/bloom-560m",
+  "bias": "none",
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+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "dense_h_to_4h",
+    "dense",
+    "dense_4h_to_h",
+    "query_key_value"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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runs/Jun29_03-42-23_1ed9159292fd/events.out.tfevents.1719632579.1ed9159292fd.612.0

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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+  "added_tokens_decoder": {
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+  "pad_token": "</s>",
+  "padding_side": "left",
+  "tokenizer_class": "BloomTokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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