End of training

.gitattributes

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 *.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 +1,64 @@
+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: bigscience/mt0-large
+model-index:
+- name: mt0-large_IA3_627_lr5e-05_bs4_epoch5_wd0.01
+  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. -->
+
+# mt0-large_IA3_627_lr5e-05_bs4_epoch5_wd0.01
+
+This model is a fine-tuned version of [bigscience/mt0-large](https://huggingface.co/bigscience/mt0-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2215
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.5849        | 1.0   | 157  | 0.3658          |
+| 0.5258        | 2.0   | 314  | 0.3299          |
+| 0.5039        | 3.0   | 471  | 0.2787          |
+| 0.414         | 4.0   | 628  | 0.2347          |
+| 0.3916        | 5.0   | 785  | 0.2215          |
+
+
+### Framework versions
+
+- PEFT 0.7.1
+- Transformers 4.36.2
+- Pytorch 2.0.1
+- Datasets 2.16.1
+- Tokenizers 0.15.0

adapter_config.json

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+  "init_ia3_weights": true,
+  "modules_to_save": null,
+  "peft_type": "IA3",
+  "revision": null,
+  "target_modules": [
+    "k",
+    "v",
+    "wi_1"
+  ],
+  "task_type": "SEQ_2_SEQ_LM"
+}

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "T5Tokenizer",
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+}

training_args.bin

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