Upload folder using huggingface_hub

checkpoint-160/README.md

@@ -0,0 +1,220 @@
+---
+library_name: peft
+base_model: mistralai/Mistral-7B-v0.1
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+
+
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_8bit: False
+- load_in_4bit: True
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: nf4
+- bnb_4bit_use_double_quant: True
+- bnb_4bit_compute_dtype: float16
+
+### Framework versions
+
+
+- PEFT 0.6.3.dev0

checkpoint-160/adapter_config.json

@@ -0,0 +1,24 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "gate_proj",
+    "down_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

checkpoint-160/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4be9432aed019cb21dde4a8664b3b2017addda5d9dcb7ca10978e6a76ef6c3a6
+size 226517904

checkpoint-160/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fb52ae3f12182b7796cfae5090fdeca5ab5f1ce8cbf395c2a233f19c959d1f1a
+size 453146810

checkpoint-160/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ad97f173cf0965a103dd11d47253176c504d4cab049e6d92b618b758287e7144
+size 14244

checkpoint-160/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a903a89ae1451aab0b2994f4d2312d91ae301ccfebccd2e4e211e0deb544c4f5
+size 1064

checkpoint-160/trainer_state.json

@@ -0,0 +1,980 @@
+{
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 2.6473629782833505,
+  "eval_steps": 500,
+  "global_step": 160,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.02,
+      "learning_rate": 4.000000000000001e-06,
+      "loss": 0.643,
+      "step": 1
+    },
+    {
+      "epoch": 0.03,
+      "learning_rate": 8.000000000000001e-06,
+      "loss": 0.6409,
+      "step": 2
+    },
+    {
+      "epoch": 0.05,
+      "learning_rate": 1.2e-05,
+      "loss": 0.5779,
+      "step": 3
+    },
+    {
+      "epoch": 0.07,
+      "learning_rate": 1.6000000000000003e-05,
+      "loss": 0.6641,
+      "step": 4
+    },
+    {
+      "epoch": 0.08,
+      "learning_rate": 2e-05,
+      "loss": 0.61,
+      "step": 5
+    },
+    {
+      "epoch": 0.1,
+      "learning_rate": 2.4e-05,
+      "loss": 0.6653,
+      "step": 6
+    },
+    {
+      "epoch": 0.12,
+      "learning_rate": 2.8000000000000003e-05,
+      "loss": 0.6101,
+      "step": 7
+    },
+    {
+      "epoch": 0.13,
+      "learning_rate": 3.2000000000000005e-05,
+      "loss": 0.7479,
+      "step": 8
+    },
+    {
+      "epoch": 0.15,
+      "learning_rate": 3.6e-05,
+      "loss": 0.6357,
+      "step": 9
+    },
+    {
+      "epoch": 0.17,
+      "learning_rate": 4e-05,
+      "loss": 0.6214,
+      "step": 10
+    },
+    {
+      "epoch": 0.18,
+      "learning_rate": 4.4000000000000006e-05,
+      "loss": 0.6257,
+      "step": 11
+    },
+    {
+      "epoch": 0.2,
+      "learning_rate": 4.8e-05,
+      "loss": 0.6228,
+      "step": 12
+    },
+    {
+      "epoch": 0.22,
+      "learning_rate": 5.2000000000000004e-05,
+      "loss": 0.6295,
+      "step": 13
+    },
+    {
+      "epoch": 0.23,
+      "learning_rate": 5.6000000000000006e-05,
+      "loss": 0.6345,
+      "step": 14
+    },
+    {
+      "epoch": 0.25,
+      "learning_rate": 6e-05,
+      "loss": 0.6282,
+      "step": 15
+    },
+    {
+      "epoch": 0.26,
+      "learning_rate": 6.400000000000001e-05,
+      "loss": 0.6231,
+      "step": 16
+    },
+    {
+      "epoch": 0.28,
+      "learning_rate": 6.800000000000001e-05,
+      "loss": 0.6282,
+      "step": 17
+    },
+    {
+      "epoch": 0.3,
+      "learning_rate": 7.2e-05,
+      "loss": 0.6423,
+      "step": 18
+    },
+    {
+      "epoch": 0.31,
+      "learning_rate": 7.6e-05,
+      "loss": 0.6055,
+      "step": 19
+    },
+    {
+      "epoch": 0.33,
+      "learning_rate": 8e-05,
+      "loss": 0.6244,
+      "step": 20
+    },
+    {
+      "epoch": 0.35,
+      "learning_rate": 8.4e-05,
+      "loss": 0.5443,
+      "step": 21
+    },
+    {
+      "epoch": 0.36,
+      "learning_rate": 8.800000000000001e-05,
+      "loss": 0.6479,
+      "step": 22
+    },
+    {
+      "epoch": 0.38,
+      "learning_rate": 9.200000000000001e-05,
+      "loss": 0.5565,
+      "step": 23
+    },
+    {
+      "epoch": 0.4,
+      "learning_rate": 9.6e-05,
+      "loss": 0.6131,
+      "step": 24
+    },
+    {
+      "epoch": 0.41,
+      "learning_rate": 0.0001,
+      "loss": 0.6696,
+      "step": 25
+    },
+    {
+      "epoch": 0.43,
+      "learning_rate": 0.00010400000000000001,
+      "loss": 0.5886,
+      "step": 26
+    },
+    {
+      "epoch": 0.45,
+      "learning_rate": 0.00010800000000000001,
+      "loss": 0.5999,
+      "step": 27
+    },
+    {
+      "epoch": 0.46,
+      "learning_rate": 0.00011200000000000001,
+      "loss": 0.7083,
+      "step": 28
+    },
+    {
+      "epoch": 0.48,
+      "learning_rate": 0.000116,
+      "loss": 0.6178,
+      "step": 29
+    },
+    {
+      "epoch": 0.5,
+      "learning_rate": 0.00012,
+      "loss": 0.6466,
+      "step": 30
+    },
+    {
+      "epoch": 0.51,
+      "learning_rate": 0.000124,
+      "loss": 0.5462,
+      "step": 31
+    },
+    {
+      "epoch": 0.53,
+      "learning_rate": 0.00012800000000000002,
+      "loss": 0.6239,
+      "step": 32
+    },
+    {
+      "epoch": 0.55,
+      "learning_rate": 0.000132,
+      "loss": 0.6646,
+      "step": 33
+    },
+    {
+      "epoch": 0.56,
+      "learning_rate": 0.00013600000000000003,
+      "loss": 0.6293,
+      "step": 34
+    },
+    {
+      "epoch": 0.58,
+      "learning_rate": 0.00014,
+      "loss": 0.5853,
+      "step": 35
+    },
+    {
+      "epoch": 0.6,
+      "learning_rate": 0.000144,
+      "loss": 0.6881,
+      "step": 36
+    },
+    {
+      "epoch": 0.61,
+      "learning_rate": 0.000148,
+      "loss": 0.6398,
+      "step": 37
+    },
+    {
+      "epoch": 0.63,
+      "learning_rate": 0.000152,
+      "loss": 0.6054,
+      "step": 38
+    },
+    {
+      "epoch": 0.65,
+      "learning_rate": 0.00015600000000000002,
+      "loss": 0.6332,
+      "step": 39
+    },
+    {
+      "epoch": 0.66,
+      "learning_rate": 0.00016,
+      "loss": 0.5941,
+      "step": 40
+    },
+    {
+      "epoch": 0.68,
+      "learning_rate": 0.000164,
+      "loss": 0.6127,
+      "step": 41
+    },
+    {
+      "epoch": 0.69,
+      "learning_rate": 0.000168,
+      "loss": 0.6475,
+      "step": 42
+    },
+    {
+      "epoch": 0.71,
+      "learning_rate": 0.000172,
+      "loss": 0.5668,
+      "step": 43
+    },
+    {
+      "epoch": 0.73,
+      "learning_rate": 0.00017600000000000002,
+      "loss": 0.6348,
+      "step": 44
+    },
+    {
+      "epoch": 0.74,
+      "learning_rate": 0.00018,
+      "loss": 0.6379,
+      "step": 45
+    },
+    {
+      "epoch": 0.76,
+      "learning_rate": 0.00018400000000000003,
+      "loss": 0.5992,
+      "step": 46
+    },
+    {
+      "epoch": 0.78,
+      "learning_rate": 0.000188,
+      "loss": 0.6435,
+      "step": 47
+    },
+    {
+      "epoch": 0.79,
+      "learning_rate": 0.000192,
+      "loss": 0.5909,
+      "step": 48
+    },
+    {
+      "epoch": 0.81,
+      "learning_rate": 0.000196,
+      "loss": 0.6596,
+      "step": 49
+    },
+    {
+      "epoch": 0.83,
+      "learning_rate": 0.0002,
+      "loss": 0.6426,
+      "step": 50
+    },
+    {
+      "epoch": 0.84,
+      "learning_rate": 0.00020400000000000003,
+      "loss": 0.5908,
+      "step": 51
+    },
+    {
+      "epoch": 0.86,
+      "learning_rate": 0.00020800000000000001,
+      "loss": 0.5486,
+      "step": 52
+    },
+    {
+      "epoch": 0.88,
+      "learning_rate": 0.00021200000000000003,
+      "loss": 0.6184,
+      "step": 53
+    },
+    {
+      "epoch": 0.89,
+      "learning_rate": 0.00021600000000000002,
+      "loss": 0.6977,
+      "step": 54
+    },
+    {
+      "epoch": 0.91,
+      "learning_rate": 0.00022000000000000003,
+      "loss": 0.6308,
+      "step": 55
+    },
+    {
+      "epoch": 0.93,
+      "learning_rate": 0.00022400000000000002,
+      "loss": 0.5394,
+      "step": 56
+    },
+    {
+      "epoch": 0.94,
+      "learning_rate": 0.00022799999999999999,
+      "loss": 0.5426,
+      "step": 57
+    },
+    {
+      "epoch": 0.96,
+      "learning_rate": 0.000232,
+      "loss": 0.5429,
+      "step": 58
+    },
+    {
+      "epoch": 0.98,
+      "learning_rate": 0.000236,
+      "loss": 0.5822,
+      "step": 59
+    },
+    {
+      "epoch": 0.99,
+      "learning_rate": 0.00024,
+      "loss": 0.5793,
+      "step": 60
+    },
+    {
+      "epoch": 1.01,
+      "learning_rate": 0.000244,
+      "loss": 0.5906,
+      "step": 61
+    },
+    {
+      "epoch": 1.03,
+      "learning_rate": 0.000248,
+      "loss": 0.4957,
+      "step": 62
+    },
+    {
+      "epoch": 1.04,
+      "learning_rate": 0.000252,
+      "loss": 0.5421,
+      "step": 63
+    },
+    {
+      "epoch": 1.06,
+      "learning_rate": 0.00025600000000000004,
+      "loss": 0.5444,
+      "step": 64
+    },
+    {
+      "epoch": 1.08,
+      "learning_rate": 0.00026000000000000003,
+      "loss": 0.5618,
+      "step": 65
+    },
+    {
+      "epoch": 1.09,
+      "learning_rate": 0.000264,
+      "loss": 0.5372,
+      "step": 66
+    },
+    {
+      "epoch": 1.11,
+      "learning_rate": 0.000268,
+      "loss": 0.5701,
+      "step": 67
+    },
+    {
+      "epoch": 1.13,
+      "learning_rate": 0.00027200000000000005,
+      "loss": 0.5257,
+      "step": 68
+    },
+    {
+      "epoch": 1.14,
+      "learning_rate": 0.000276,
+      "loss": 0.5237,
+      "step": 69
+    },
+    {
+      "epoch": 1.16,
+      "learning_rate": 0.00028,
+      "loss": 0.4729,
+      "step": 70
+    },
+    {
+      "epoch": 1.17,
+      "learning_rate": 0.000284,
+      "loss": 0.5142,
+      "step": 71
+    },
+    {
+      "epoch": 1.19,
+      "learning_rate": 0.000288,
+      "loss": 0.5365,
+      "step": 72
+    },
+    {
+      "epoch": 1.21,
+      "learning_rate": 0.000292,
+      "loss": 0.5288,
+      "step": 73
+    },
+    {
+      "epoch": 1.22,
+      "learning_rate": 0.000296,
+      "loss": 0.5095,
+      "step": 74
+    },
+    {
+      "epoch": 1.24,
+      "learning_rate": 0.00030000000000000003,
+      "loss": 0.5229,
+      "step": 75
+    },
+    {
+      "epoch": 1.26,
+      "learning_rate": 0.000304,
+      "loss": 0.5355,
+      "step": 76
+    },
+    {
+      "epoch": 1.27,
+      "learning_rate": 0.000308,
+      "loss": 0.5626,
+      "step": 77
+    },
+    {
+      "epoch": 1.29,
+      "learning_rate": 0.00031200000000000005,
+      "loss": 0.5548,
+      "step": 78
+    },
+    {
+      "epoch": 1.31,
+      "learning_rate": 0.00031600000000000004,
+      "loss": 0.5404,
+      "step": 79
+    },
+    {
+      "epoch": 1.32,
+      "learning_rate": 0.00032,
+      "loss": 0.5686,
+      "step": 80
+    },
+    {
+      "epoch": 1.34,
+      "learning_rate": 0.000324,
+      "loss": 0.5242,
+      "step": 81
+    },
+    {
+      "epoch": 1.36,
+      "learning_rate": 0.000328,
+      "loss": 0.52,
+      "step": 82
+    },
+    {
+      "epoch": 1.37,
+      "learning_rate": 0.000332,
+      "loss": 0.5481,
+      "step": 83
+    },
+    {
+      "epoch": 1.39,
+      "learning_rate": 0.000336,
+      "loss": 0.5321,
+      "step": 84
+    },
+    {
+      "epoch": 1.41,
+      "learning_rate": 0.00034,
+      "loss": 0.603,
+      "step": 85
+    },
+    {
+      "epoch": 1.42,
+      "learning_rate": 0.000344,
+      "loss": 0.4836,
+      "step": 86
+    },
+    {
+      "epoch": 1.44,
+      "learning_rate": 0.000348,
+      "loss": 0.5583,
+      "step": 87
+    },
+    {
+      "epoch": 1.46,
+      "learning_rate": 0.00035200000000000005,
+      "loss": 0.5336,
+      "step": 88
+    },
+    {
+      "epoch": 1.47,
+      "learning_rate": 0.00035600000000000003,
+      "loss": 0.4061,
+      "step": 89
+    },
+    {
+      "epoch": 1.49,
+      "learning_rate": 0.00036,
+      "loss": 0.5555,
+      "step": 90
+    },
+    {
+      "epoch": 1.51,
+      "learning_rate": 0.000364,
+      "loss": 0.5216,
+      "step": 91
+    },
+    {
+      "epoch": 1.52,
+      "learning_rate": 0.00036800000000000005,
+      "loss": 0.4991,
+      "step": 92
+    },
+    {
+      "epoch": 1.54,
+      "learning_rate": 0.00037200000000000004,
+      "loss": 0.5601,
+      "step": 93
+    },
+    {
+      "epoch": 1.56,
+      "learning_rate": 0.000376,
+      "loss": 0.4857,
+      "step": 94
+    },
+    {
+      "epoch": 1.57,
+      "learning_rate": 0.00038,
+      "loss": 0.5439,
+      "step": 95
+    },
+    {
+      "epoch": 1.59,
+      "learning_rate": 0.000384,
+      "loss": 0.5817,
+      "step": 96
+    },
+    {
+      "epoch": 1.6,
+      "learning_rate": 0.000388,
+      "loss": 0.5179,
+      "step": 97
+    },
+    {
+      "epoch": 1.62,
+      "learning_rate": 0.000392,
+      "loss": 0.5464,
+      "step": 98
+    },
+    {
+      "epoch": 1.64,
+      "learning_rate": 0.00039600000000000003,
+      "loss": 0.513,
+      "step": 99
+    },
+    {
+      "epoch": 1.65,
+      "learning_rate": 0.0004,
+      "loss": 0.4899,
+      "step": 100
+    },
+    {
+      "epoch": 1.67,
+      "learning_rate": 0.0003998458072481446,
+      "loss": 0.5715,
+      "step": 101
+    },
+    {
+      "epoch": 1.69,
+      "learning_rate": 0.0003993834667466256,
+      "loss": 0.5312,
+      "step": 102
+    },
+    {
+      "epoch": 1.7,
+      "learning_rate": 0.0003986136913909853,
+      "loss": 0.5066,
+      "step": 103
+    },
+    {
+      "epoch": 1.72,
+      "learning_rate": 0.00039753766811902755,
+      "loss": 0.5407,
+      "step": 104
+    },
+    {
+      "epoch": 1.74,
+      "learning_rate": 0.0003961570560806461,
+      "loss": 0.5281,
+      "step": 105
+    },
+    {
+      "epoch": 1.75,
+      "learning_rate": 0.0003944739840795353,
+      "loss": 0.4873,
+      "step": 106
+    },
+    {
+      "epoch": 1.77,
+      "learning_rate": 0.00039249104729072946,
+      "loss": 0.5336,
+      "step": 107
+    },
+    {
+      "epoch": 1.79,
+      "learning_rate": 0.00039021130325903074,
+      "loss": 0.4842,
+      "step": 108
+    },
+    {
+      "epoch": 1.8,
+      "learning_rate": 0.00038763826718449685,
+      "loss": 0.5136,
+      "step": 109
+    },
+    {
+      "epoch": 1.82,
+      "learning_rate": 0.0003847759065022574,
+      "loss": 0.5359,
+      "step": 110
+    },
+    {
+      "epoch": 1.84,
+      "learning_rate": 0.0003816286347650163,
+      "loss": 0.4766,
+      "step": 111
+    },
+    {
+      "epoch": 1.85,
+      "learning_rate": 0.0003782013048376736,
+      "loss": 0.4896,
+      "step": 112
+    },
+    {
+      "epoch": 1.87,
+      "learning_rate": 0.00037449920141455944,
+      "loss": 0.4977,
+      "step": 113
+    },
+    {
+      "epoch": 1.89,
+      "learning_rate": 0.00037052803287081844,
+      "loss": 0.506,
+      "step": 114
+    },
+    {
+      "epoch": 1.9,
+      "learning_rate": 0.0003662939224605091,
+      "loss": 0.5442,
+      "step": 115
+    },
+    {
+      "epoch": 1.92,
+      "learning_rate": 0.0003618033988749895,
+      "loss": 0.5445,
+      "step": 116
+    },
+    {
+      "epoch": 1.94,
+      "learning_rate": 0.00035706338617614897,
+      "loss": 0.5348,
+      "step": 117
+    },
+    {
+      "epoch": 1.95,
+      "learning_rate": 0.0003520811931200062,
+      "loss": 0.5331,
+      "step": 118
+    },
+    {
+      "epoch": 1.97,
+      "learning_rate": 0.0003468645018871371,
+      "loss": 0.4697,
+      "step": 119
+    },
+    {
+      "epoch": 1.99,
+      "learning_rate": 0.0003414213562373095,
+      "loss": 0.5119,
+      "step": 120
+    },
+    {
+      "epoch": 2.0,
+      "learning_rate": 0.0003357601491065884,
+      "loss": 0.4679,
+      "step": 121
+    },
+    {
+      "epoch": 2.02,
+      "learning_rate": 0.0003298896096660367,
+      "loss": 0.3522,
+      "step": 122
+    },
+    {
+      "epoch": 2.04,
+      "learning_rate": 0.00032381878986196687,
+      "loss": 0.3267,
+      "step": 123
+    },
+    {
+      "epoch": 2.05,
+      "learning_rate": 0.00031755705045849464,
+      "loss": 0.3626,
+      "step": 124
+    },
+    {
+      "epoch": 2.07,
+      "learning_rate": 0.00031111404660392046,
+      "loss": 0.3274,
+      "step": 125
+    },
+    {
+      "epoch": 2.08,
+      "learning_rate": 0.0003044997129431898,
+      "loss": 0.3159,
+      "step": 126
+    },
+    {
+      "epoch": 2.1,
+      "learning_rate": 0.00029772424829939106,
+      "loss": 0.3336,
+      "step": 127
+    },
+    {
+      "epoch": 2.12,
+      "learning_rate": 0.00029079809994790937,
+      "loss": 0.2973,
+      "step": 128
+    },
+    {
+      "epoch": 2.13,
+      "learning_rate": 0.0002837319475074856,
+      "loss": 0.319,
+      "step": 129
+    },
+    {
+      "epoch": 2.15,
+      "learning_rate": 0.000276536686473018,
+      "loss": 0.2978,
+      "step": 130
+    },
+    {
+      "epoch": 2.17,
+      "learning_rate": 0.0002692234114154986,
+      "loss": 0.3393,
+      "step": 131
+    },
+    {
+      "epoch": 2.18,
+      "learning_rate": 0.00026180339887498953,
+      "loss": 0.3318,
+      "step": 132
+    },
+    {
+      "epoch": 2.2,
+      "learning_rate": 0.00025428808997301485,
+      "loss": 0.299,
+      "step": 133
+    },
+    {
+      "epoch": 2.22,
+      "learning_rate": 0.00024668907277118114,
+      "loss": 0.27,
+      "step": 134
+    },
+    {
+      "epoch": 2.23,
+      "learning_rate": 0.0002390180644032257,
+      "loss": 0.2739,
+      "step": 135
+    },
+    {
+      "epoch": 2.25,
+      "learning_rate": 0.0002312868930080462,
+      "loss": 0.3041,
+      "step": 136
+    },
+    {
+      "epoch": 2.27,
+      "learning_rate": 0.00022350747949156756,
+      "loss": 0.2892,
+      "step": 137
+    },
+    {
+      "epoch": 2.28,
+      "learning_rate": 0.000215691819145569,
+      "loss": 0.2659,
+      "step": 138
+    },
+    {
+      "epoch": 2.3,
+      "learning_rate": 0.00020785196315181376,
+      "loss": 0.3424,
+      "step": 139
+    },
+    {
+      "epoch": 2.32,
+      "learning_rate": 0.0002,
+      "loss": 0.318,
+      "step": 140
+    },
+    {
+      "epoch": 2.33,
+      "learning_rate": 0.00019214803684818634,
+      "loss": 0.2428,
+      "step": 141
+    },
+    {
+      "epoch": 2.35,
+      "learning_rate": 0.00018430818085443104,
+      "loss": 0.3104,
+      "step": 142
+    },
+    {
+      "epoch": 2.37,
+      "learning_rate": 0.00017649252050843252,
+      "loss": 0.2511,
+      "step": 143
+    },
+    {
+      "epoch": 2.38,
+      "learning_rate": 0.00016871310699195379,
+      "loss": 0.3066,
+      "step": 144
+    },
+    {
+      "epoch": 2.4,
+      "learning_rate": 0.00016098193559677438,
+      "loss": 0.2746,
+      "step": 145
+    },
+    {
+      "epoch": 2.42,
+      "learning_rate": 0.000153310927228819,
+      "loss": 0.3335,
+      "step": 146
+    },
+    {
+      "epoch": 2.43,
+      "learning_rate": 0.00014571191002698517,
+      "loss": 0.324,
+      "step": 147
+    },
+    {
+      "epoch": 2.45,
+      "learning_rate": 0.00013819660112501054,
+      "loss": 0.3011,
+      "step": 148
+    },
+    {
+      "epoch": 2.47,
+      "learning_rate": 0.00013077658858450138,
+      "loss": 0.3124,
+      "step": 149
+    },
+    {
+      "epoch": 2.48,
+      "learning_rate": 0.00012346331352698205,
+      "loss": 0.3228,
+      "step": 150
+    },
+    {
+      "epoch": 2.5,
+      "learning_rate": 0.00011626805249251445,
+      "loss": 0.2771,
+      "step": 151
+    },
+    {
+      "epoch": 2.51,
+      "learning_rate": 0.00010920190005209065,
+      "loss": 0.2801,
+      "step": 152
+    },
+    {
+      "epoch": 2.53,
+      "learning_rate": 0.00010227575170060909,
+      "loss": 0.3216,
+      "step": 153
+    },
+    {
+      "epoch": 2.55,
+      "learning_rate": 9.550028705681025e-05,
+      "loss": 0.2793,
+      "step": 154
+    },
+    {
+      "epoch": 2.56,
+      "learning_rate": 8.888595339607961e-05,
+      "loss": 0.2758,
+      "step": 155
+    },
+    {
+      "epoch": 2.58,
+      "learning_rate": 8.24429495415054e-05,
+      "loss": 0.2924,
+      "step": 156
+    },
+    {
+      "epoch": 2.6,
+      "learning_rate": 7.618121013803319e-05,
+      "loss": 0.3309,
+      "step": 157
+    },
+    {
+      "epoch": 2.61,
+      "learning_rate": 7.011039033396329e-05,
+      "loss": 0.2523,
+      "step": 158
+    },
+    {
+      "epoch": 2.63,
+      "learning_rate": 6.423985089341164e-05,
+      "loss": 0.2719,
+      "step": 159
+    },
+    {
+      "epoch": 2.65,
+      "learning_rate": 5.857864376269051e-05,
+      "loss": 0.2896,
+      "step": 160
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 180,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 10,
+  "total_flos": 5.54372727422976e+17,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-160/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f924836ef21707286fc6978ae0980c72a4e9c41410a8b98d6d3ba75f7357b705
+size 4664

runs/Nov24_16-17-54_924075f44444/events.out.tfevents.1700842675.924075f44444.7554.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8ae76810e230c071dcfc575a859bea83425bfd0ecf0af816f4da24c1e6695625
-size 27890
+oid sha256:2b54d1576b2f8f470d3107b9f90c383603351130c5f26db92e132118290b7516
+size 29460