End of training

README.md

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+---
+license: apache-2.0
+base_model: ibm/TTM
+tags:
+- generated_from_trainer
+model-index:
+- name: fewshot_5
+  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. -->
+
+# fewshot_5
+
+This model is a fine-tuned version of [ibm/TTM](https://huggingface.co/ibm/TTM) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0422
+
+## 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: 0.001
+- train_batch_size: 512
+- eval_batch_size: 512
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.2328        | 1.0   | 24   | 0.0388          |
+| 0.2256        | 2.0   | 48   | 0.0388          |
+| 0.2207        | 3.0   | 72   | 0.0386          |
+| 0.2165        | 4.0   | 96   | 0.0386          |
+| 0.2132        | 5.0   | 120  | 0.0386          |
+| 0.2084        | 6.0   | 144  | 0.0387          |
+| 0.2033        | 7.0   | 168  | 0.0392          |
+| 0.1971        | 8.0   | 192  | 0.0400          |
+| 0.1911        | 9.0   | 216  | 0.0412          |
+| 0.1836        | 10.0  | 240  | 0.0422          |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "ibm/TTM",
+  "adaptive_patching_levels": 3,
+  "architectures": [
+    "TinyTimeMixerForPrediction"
+  ],
+  "context_length": 1024,
+  "d_model": 192,
+  "d_model_scale": 3,
+  "decoder_adaptive_patching_levels": 0,
+  "decoder_d_model": 128,
+  "decoder_d_model_scale": 2,
+  "decoder_mode": "common_channel",
+  "decoder_num_layers": 2,
+  "decoder_raw_residual": false,
+  "dropout": 0.2,
+  "expansion_factor": 2,
+  "frequency_token_vocab_size": 5,
+  "gated_attn": true,
+  "head_dropout": 0.2,
+  "init_processing": true,
+  "init_std": 0.02,
+  "loss": "mse",
+  "mode": "common_channel",
+  "model_type": "tinytimemixer",
+  "norm_eps": 1e-05,
+  "norm_mlp": "LayerNorm",
+  "num_input_channels": 1,
+  "num_layers": 2,
+  "num_patches": 16,
+  "patch_last": true,
+  "patch_length": 64,
+  "patch_stride": 64,
+  "positional_encoding_type": "sincos",
+  "post_init": false,
+  "prediction_channel_indices": null,
+  "prediction_filter_length": null,
+  "prediction_length": 96,
+  "resolution_prefix_tuning": false,
+  "scaling": "std",
+  "self_attn": false,
+  "self_attn_heads": 1,
+  "stride_ratio": 1,
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.1",
+  "use_decoder": true,
+  "use_positional_encoding": false
+}

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training_args.bin

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