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README.md

@@ -1,3 +1,61 @@
 ---
-license: afl-3.0
+language:
+- yo
+- yor
+license: apache-2.0
+base_model: google/byt5-small
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+model-index:
+- name: byt5_yo_yor
+  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. -->
+
+# byt5_yo_yor
+
+This model is a fine-tuned version of [google/byt5-small](https://huggingface.co/google/byt5-small) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1325
+- Bleu: 53.7855
+- Gen Len: 116.0291
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.11.0
+- Tokenizers 0.13.3

all_results.json

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+    "eval_bleu": 53.7855,
+    "eval_gen_len": 116.0291,
+    "eval_loss": 0.1324535459280014,
+    "eval_runtime": 257.6477,
+    "eval_samples": 1100,
+    "eval_samples_per_second": 4.269,
+    "eval_steps_per_second": 0.268,
+    "predict_bleu": 52.4695,
+    "predict_gen_len": 122.65,
+    "predict_loss": 0.14169275760650635,
+    "predict_runtime": 263.0404,
+    "predict_samples": 1100,
+    "predict_samples_per_second": 4.182,
+    "predict_steps_per_second": 0.262,
+    "train_loss": 0.2496061805177381,
+    "train_runtime": 2390.8058,
+    "train_samples": 17900,
+    "train_samples_per_second": 22.461,
+    "train_steps_per_second": 1.404
+}

config.json

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+  "architectures": [
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+  "d_kv": 64,
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+  "feed_forward_proj": "gated-gelu",
+  "gradient_checkpointing": false,
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "is_gated_act": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "num_decoder_layers": 4,
+  "num_heads": 6,
+  "num_layers": 12,
+  "pad_token_id": 0,
+  "relative_attention_max_distance": 128,
+  "relative_attention_num_buckets": 32,
+  "tie_word_embeddings": false,
+  "tokenizer_class": "ByT5Tokenizer",
+  "torch_dtype": "float32",
+  "transformers_version": "4.31.0",
+  "use_cache": true,
+  "vocab_size": 384
+}

eval_results.json

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+    "eval_bleu": 53.7855,
+    "eval_gen_len": 116.0291,
+    "eval_loss": 0.1324535459280014,
+    "eval_runtime": 257.6477,
+    "eval_samples": 1100,
+    "eval_samples_per_second": 4.269,
+    "eval_steps_per_second": 0.268
+}

generation_config.json

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+  "decoder_start_token_id": 0,
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+  "pad_token_id": 0,
+  "transformers_version": "4.31.0"
+}

predict_results.json

@@ -0,0 +1,9 @@
+{
+    "predict_bleu": 52.4695,
+    "predict_gen_len": 122.65,
+    "predict_loss": 0.14169275760650635,
+    "predict_runtime": 263.0404,
+    "predict_samples": 1100,
+    "predict_samples_per_second": 4.182,
+    "predict_steps_per_second": 0.262
+}

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