filnow/nlg-umt5-pol

README.md

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+---
+license: apache-2.0
+base_model: google/umt5-small
+tags:
+- generated_from_trainer
+model-index:
+- name: working
+  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. -->
+
+# working
+
+This model is a fine-tuned version of [google/umt5-small](https://huggingface.co/google/umt5-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2312
+
+## 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: 8
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.7329        | 1.0   | 2321 | 0.3316          |
+| 0.3731        | 2.0   | 4642 | 0.2464          |
+| 0.3269        | 3.0   | 6963 | 0.2312          |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.1.2
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "google/umt5-small",
+  "architectures": [
+    "UMT5ForConditionalGeneration"
+  ],
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+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "gated-gelu",
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+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "max_new_tokens": 64,
+  "model_type": "umt5",
+  "num_decoder_layers": 8,
+  "num_heads": 6,
+  "num_layers": 8,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "scalable_attention": true,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "T5Tokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.1",
+  "use_cache": true,
+  "vocab_size": 256384
+}

generation_config.json

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+{
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+  "eos_token_id": 1,
+  "max_new_tokens": 64,
+  "pad_token_id": 0,
+  "transformers_version": "4.41.1"
+}

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runs/Jun03_11-19-32_743112a2decd/events.out.tfevents.1717413574.743112a2decd.34.0

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training_args.bin

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wandb/run-20240603_111947-zd4tutif/files/output.log

@@ -0,0 +1,8 @@
+
+There were missing keys in the checkpoint model loaded: ['encoder.embed_tokens.weight', 'decoder.embed_tokens.weight'].
+Your max_length is set to 20, but your input_length is only 10. Since this is a summarization task, where outputs shorter than the input are typically wanted, you might consider decreasing max_length manually, e.g. summarizer('...', max_length=5)
+Your max_length is set to 20, but your input_length is only 14. Since this is a summarization task, where outputs shorter than the input are typically wanted, you might consider decreasing max_length manually, e.g. summarizer('...', max_length=7)
+Your max_length is set to 20, but your input_length is only 16. Since this is a summarization task, where outputs shorter than the input are typically wanted, you might consider decreasing max_length manually, e.g. summarizer('...', max_length=8)
+The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.
+Token is valid (permission: write).
+Your token has been saved to /root/.cache/huggingface/token

wandb/run-20240603_111947-zd4tutif/files/requirements.txt

@@ -0,0 +1,868 @@
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wandb/run-20240603_111947-zd4tutif/files/wandb-metadata.json

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